Message queues determine how your network functions. But many networks’ message queue infrastructures are surprisingly fragile. When one link on the chain fails, the entire system can function unexpectedly, or even fail outright.
To prevent these problems, you need to make sure your message queue is fail-safe — and harnessing the power of the Cloud is one of the best ways to do this. Read on to learn why your message queue’s proper function is so important, and how the Cloud can help you assure your network’s integrity.
The Importance of Your Message Queue
A message queue is very different from your email inbox, or a comparable human message queue. It helps different components within a system communicate with each other, in ways that can affect the network’s overall function and performance.
No matter what field you’re in or what your network does, the different parts of your network constantly send messages to each other. These may be requests for information (such as long polling), error messages, alerts, triggers which cause a component to perform an action, task queues, and more.
These messages assure the normal function of your network and its components, and every message is important. If even one gets lost along the way, this can cause components to behave in unexpected ways.
This can be inconvenient at best, and in the cases of critical systems — such as those monitoring the well-being of important components in heavy industry applications — it can even be dangerous. For instance, if a sensor sends an alarm notification to a switch, saying the temperature in a given furnace is too hot, the switch may trigger a shutdown. But the message never gets through, that automated shutdown function may not occur.
Unfortunately, even brief interruptions in network connectivity can affect the overall integrity of your system. If these messages don’t go through or are delayed, or if part of your system suffers some interruption and loses some or all of its message queue, this can be enough to upend your network’s normal function.
The Power of the Cloud
All of these problems pose unique challenges to system administrators. However, the advent of Cloud message storage and connectivity, through services like IronMQ, has transformed network administrators’ ability to ensure the integrity and healthy functioning of their systems.
Companies who subscribe to IronMQ’s service can host their message queues on Iron.io’s dedicated servers. Messages go to and from the queue Iron.io hosts, rather than being stored locally. Because Iron.io’s network is fully redundant, and the company is committed to ensuring the continuous uptime of these servers, your network has a fail-safe message queue — without you investing thousands of dollars into your digital infrastructure.
IronMQ’s Cloud-based servers also offer many functionalities other message queue software doesn’t. For instance, IronMQ offers Webhook support, and can create push queues to cause components to perform various tasks. The system offers a human-readable dashboard, and full reporting and analytics. Plus, for networks where security is an issue, IronMQ allows client-side implementation.
When a network suffers the loss of some or all messages from a queue, this can negatively affect the network’s components’ function, in ways that can even be dangerous in certain settings. By relying on a Cloud-based message queue service like IronMQ, you can rest assured that all your network’s messages will get through.
The term “DevOps” is a phrase that was coined by Patrick Debois approximately ten years ago. It is used to describe the methodology behind operation and development engineers working together from design to development. Developing a strong understanding of DevOps allows you to experience improvements regarding the efficiency and quality of the development of your mobile application. What does that mean in terms of the future of DevOps? In the coming years, we can expect to see some significant changes.
Mark Debney from 6poin6 writes, “Whilst DevOps culture will be integrated into development teams. For those of us with DevOps in our job title, I see the role evolving into a cloud specialty with a focus on optimising the usage of cloud technologies, working as specialist centralised development teams creating tools to augment and aid the development process, providing guidance and best practice across an organisation’s rapidly changing cloud estate.”
What is DevOps?
DevOps is a combination of software development and information technology operations that enables businesses to deliver applications at a faster pace. It brings together development and operations teams so there are fewer redundancies in the software development process.
There was a growing divide between the product’s creation and its support before the world of DevOps. The silos led to delays in production. Even after Agile methodology got customers, developers, managers, and QA working together, operations, and infrastructure wasn’t addressed. The product’s delivery and infrastructure can be seen as an extension of Agile when looking at DevOps.
DevOps: What is the CALMS Model?
The CALMS model is essentially the framework for DevOps, and it was created by Damon Edwards and John Willis, authors of the DevOps Cafe podcast, in 2010. CALMS is an acronym for Culture, Automation, Lean, Measurement, and Sharing.
Culture: focuses on people and embraces change and experimentation.
Automation: is continuous delivery with infrastructure as code.
Lean: focuses on producing value for the end-user utilizing small batches.
Measurement: measures everything while simultaneously showing the improvements.
Sharing: open information sharing using collaboration and communication.
Daniel Greene of TechCrunch writes, “You can visualize DevOps as a conveyor belt, where many checks and balances are in place, at all stages, to ensure any bundle coming down the belt is removed if it’s not good enough and delivered to the end of the belt (e.g. production) safely and reliably if it is.”
What Does This Mean for the Future of DevOps?
ne of the critical new standards when it comes to product development is cloud computing. Cloud computing calls for a separation between development and deployment. In turn, it makes a DevOps pipeline crucial to a business for maintaining that separation. As software continues to depend more and more on multiple clouds, it will lead to containerization of software. As a result, traditional functions of DevOps are expected to see a dramatic shift.
For one, as the industry continues making shifts toward software management using standardized frameworks, DevOps professionals will have more time to drive efficient innovations. These professionals will also have more time to tackle the challenges they face regarding managing large clusters of complex applications across technology stacks.
Two, DevOps professionals will need to respond to changing technologies as multi-cloud environments mature and evolve. These professionals will also be responding to the power of these platforms and making adaptations to ensure their software is getting the most benefits out of them. They will also need to understand the cloud platform’s native features and communicate them to their teams. That way, they can minimize the amount of work occurring throughout the deployment.
What Are the Trends Regarding DevOps?
Growing trends are also occurring in the world of cloud computing and it’s relationship to DevOps:
There’s an increase in diversity of cloud services which are leading to multi-could and hybrid infrastructures.
Data managers are facing more requirements regarding the emergence of DataOps.
Kit Merker writes, “The emerging methods of DataOps draw directly from the key principles of DevOps — automation to help distributed teams support frequent and continuous integration and delivery. In the same way that DevOps helps developers, quality assurance, and operations to smoothly and securely collaborate, DataOps provides the same benefits to the joint efforts of developers, data scientists, data engineers, and operations.”
When more than one cloud management platform is utilized in a single IT environment, it’s a multi-could accommodation. This occurs for several reasons, including:
to minimize downtime through redundancy
reduce data loss and sprawl
avoid vendor lock-in
provide versatility to meet a team’s varying project needs
As a result, DevOps teams must work toward meeting multi-cloud needs by becoming more scalable and Agile. It’s possible to achieve this goal utilizing continuous release and integration, as well as automation.
There may be problems with DevOps attempting to keep up by continuing to do the same thing, but quicker. The main reason is traditional DevOps apps are monolithic. Therefore, cloud-based applications are wiser to use. That way, they’re easier to scale, automate, and move.
DevOps is becoming an industry standard for many businesses. According to a report issued by Capgemini, 60% of businesses either adopted DevOps or planned to do so during 2018. Statistics like this one demonstrates that DevOps is a necessary part of your business plan if you expect to respond quickly to the demands of the market, improve your business’s time-to-market, and keep your software solutions updated regularly.
Many businesses wonder if automation can be continuous, on-demand, always optimal, and contextual. Do you know the six “C’s” of the DevOps cycle? Understanding this cycle will help you apply them better between the different stages of automation. Here they are:
Continuous Business Planning
Sustained Release and Deployment
Collaborative Customer Feedback & Optimization
Smart implementation of automation means continuous updates of the DevOps structure can occur as developers deliver content to users despite changes. However, it also means a DevOp’s work is on-going. Automation is going to continue taking hold in the future of DevOps. The problem is many organizations are automating too much. As a result, communications are breaking down among teams.
As the industry continues to grow, more DevOps automation tools are going to roll out. That’s where developers will need skills to know which ones possess features that can be automated and which require an engineer. Otherwise, businesses will find themselves implementing what is new and causing problems with automation instead of making it work to their benefit.
These needs will eventually be met by AIOps, which stands for artificial intelligence for IT operations. Organizations must understand that automation has reached a point of inflection regarding adoption and implementation. Because of this it’s not yet subsumed by AIOps. As a result, it makes sense to carefully examine how automation should be utilized to meet demands better.
Torsten Volk, managing research director for containers, DevOps, machine learning, and AI at Enterprise Management Associates, states, “The future of DevOps requires what I like to call ‘continuous everything.’ This means that security, compliance, performance, usability, cost, and all other critical software components are automatically and continuously implemented without slowing down the release process. In short, the optimal DevOps process is fully automated and directly synchronized with rapidly changing corporate requirements.”
Code Will Become a Required Skill
Statistics indicate that, as of 2018, 86% of businesses have either implemented DevOps or plan to do so. As a result, this means organizations must invest in their DevOps engineers. However, due to the quick pace, technologies are changing, it’s challenging for individuals and businesses to keep up with their DevOps skills.
The following three categories will help DevOps professionals gain a sturdy grip on cultivating their expertise:
Ability: This is the level at which a DevOps professional can perform their tasks. Ability is natural, as opposed to skills and knowledge which are learned. Often, many DevOps professionals currently working in the field possess natural abilities.
Knowledge: This is something that’s learned. For example, a DevOps professional is born with the knowledge of the inner-workings of Jenkins. Therefore, they must obtain knowledge of it using instruction and personal study. It’s critical for DevOps professionals to continuously learn, review, and understand the latest information regarding DevOps best practices, systems, and technologies.
Skill: This is something that is learned through experience or training. Ultimately, DevOps professionals are applying what knowledge they’ve obtained to situations they’re experiencing in real-life. These skills can only be further improved by a DevOps professional with practice.
Learning Code: The Critical Need
One of the most significant demands in DevOps is testers who know how to code and automate scripts. They do this to test various cases. If you’re not sure how these skills, the recommendation is that you learn how to code immediately. You’ll find that, when you understand the various tools for DevOps and how to automate scripts, these skills play a critical role in today’s software development.
The expectation is that, if testers don’t learn code within their automated scripts, they’ll perish. Manual testing is time-consuming, and the expectation is that it will become obsolete before 2020. Automation not only ensures the market receives features faster, but it also increases the efficiency in testing.
According to Andrae Raymond, programmer and software consultant at Software Stewards, “When proper tests are in place, you can rest assured that each function is doing what it was written to do. From all stages from development to deployment we can run tests to make sure the entire system is intact with new features.”
Coding Creates Security Barriers
DevOps engineers can also write and deploy secure code quickly. In doing so, they’re protecting businesses from unwanted attacks. They’re also ensuring applications and systems have a defense mechanism in place to protect against the most common cybersecurity vulnerabilities.
Engineers will find that coding is an on-going process that undergoes many changes and updates. Therefore, a DevOps engineer must have flexibility. What that means is they’re continuously integrating and developing new operations and systems into code. While doing this, they’ll be utilizing flexible working skills and adapting to the code’s changes.
It’s also vital that engineers are comfortable with moving from various areas of a software construction to another. No matter if it’s deployment, integration, testing, or releasing–they must be able to move seamlessly.
Because code is continuously changing, engineers are also required to make on-the-spot decisions. They’ll be fixing incoherent code elements and, as a result, quick decisions are required. These coding changes must occur rapidly to ensure development and deployment can occur. It’s this kind of confidence that makes a successful coding engineer.
Security Implementation Will be a Driver
Security plays a significant role in the world of DevOps. The more automation occurs, the more problems can arise. That means, the more connected we become, the more exposure we also create.
What are the Benefits of Security Implementation?
Improvements in the effectiveness and efficiency of operations.
Teams across the company experience healthier and stronger collaborations.
Security teams experience stronger agility.
Quality assurance and automated builds have a more conducive environment.
Easier to identify vulnerabilities for applications and systems.
More freedom to focus on high-value projects.
The cloud experiences improved scalability.
An increase in the company’s ROI.
Make Security a Priority
Because DevOps practices are driven by (CI/CD) integrations and deployments that occur continuously, big releases are replaced by faster, agile release cycles. It’s possible to address your customer’s needs and demands daily by using the CI/CD pipeline to employ rapid changes. Because it’s possible to automate the CI/CD pipeline, security must be a priority. Therefore, it cannot be thought of as an add-on feature. Instead, it must be included in the software’s design.
Anthony Israel-Davis writes, “As with prevention, DevOps is uniquely positioned to take advantage of detective controls. In traditional IT environments, detection tends to be a runtime concern, with DevOps, detection, correction, and prevention can be wrapped into the pipeline itself before anything hits the production environment.”
Even though DevOps and security have always worked in conjunction with each other, you must ensure your developers are using the same software packages, dependencies, and environments throughout the software development process. The expectation is that, as DevOps continues growing in the world of IT and being adapted globally, more focus will be placed on it in the fields of cloud computing, IoT, and security.
Expect Some Challenges
Despite solving many challenges throughout the software development process, DevOps security does introduce new ones. According to a survey conducted by SANS, fewer than 46% of IT security professionals are “confronting security risks upfront in requirements and service design in 2018–and only half of respondents are fixing major vulnerabilities.”
As a result, environments end up with an uncoordinated, reactive approach to incident mitigation and management. Under many circumstances, this lack of coordination isn’t apparent until incidents occur, and a system attack or break occurs.
Security breaches can reap havoc on systems that have long-term effects. One example of a massive breach is Uber’s in late 2016. Two hackers broke into the company’s network, stealing personal data, including names, email addresses, and phone numbers of 57 million Uber users. During this breach, the hackers also stole the driver’s license numbers of 600,000 Uber drivers. According to Bloomberg, they used Uber’s GitHub account, which is where Uber’s engineers track projects and store code, to obtain the username and password. Then, they were able to access Uber’s data that was stored in one of Amazon’s servers.
Security is Everyone’s Responsibility
Jayne Groll, co-founder, and CEO of the DevOps Institute states, “DevSecOps basically says security is everybody’s responsibility with security as code. We need to start testing security much earlier in the cycle rather than making it a downstream activity. I think the security community is starting to embrace that from a tools perspective and for their personal future. I think two years from now we are going to see security as code being the norm.”
The problem with this security breach is Uber paid off the hackers to keep them quiet. However, it wasn’t long until the data breach was eventually discovered. At that point, it became a nightmare regarding public relations. Dara Khosrowshahi, Uber’s C.E.O. at the time of the hack, indicated in a statement, “While I can’t erase the past, I can commit on behalf of every Uber employee that we will learn from our mistakes.” Khosrowshahi remains on Uber’s board of directors.
When a DevOps environment is running securely, it’s operating on different policies, processes, and tools to facilitate secure and rapid releases. Use the Uber example, there needed to be a final scan to ensure there were no credentials left embedded anywhere in the code. When these pieces come together, they provide a bulletproof security system throughout the development, release, and management phases of the application.
That’s where DevSecOps comes into play. DevSecOps is a combination of both security and privacy. It’s where security is implemented into the design lifecycle of software development. In doing so, there are fewer vulnerabilities. These security features also help bring security features closer to meeting business objectives and IT standards. Use of these models helps ensure everyone is responsible for security.
Protection Against New Risks
DevSecOps offers protections against the new types of risks found when introducing CI/CD within the testing framework of DevOps. Security checks are now integrated into the process while building the code. DevSecOps covers the analysis of code, automated security controls, and post-deployment monitoring. Because DevOps professionals remain engaged throughout the process, they’ll find and mitigate issues before launching.
As a result, the development process is a more cohesive experience, as well as an improved user experience. Thanks to the improvements in the delivery chain, users receive feature updates quicker, more secure software, and they no longer have to deal with technology that lags.
Microservice Architecture Will Increase in Demand
Lately, microservices and DevOps are synonymous with each other. When you need an architectural approach to building applications, microservices provide this solution. Because microservices provide an architectural framework that is loosely coupled and distributed, the entire app won’t break when one team makes changes. One of the most significant benefits for using microservices is that it’s possible for development teams to build new components of apps rapidly. That way, they can continuously meet the ever-evolving business market.
Adam Bertram of CIO writes, “Microservices is especially useful for businesses that do not have a pre-set idea of the array of devices its applications will support. By being device- and platform-agnostic, microservices enables businesses to develop applications that provide consistent user experiences across a range of platforms, spanning the web, mobile, IoT, wearables, and fitness tracker environments. Netflix, PayPal, Amazon, eBay, and Twitter are just a few enterprises currently using microservices.”
What are the Benefits of Microservices Architecture?
The expectation is that companies are going to move to use microservices architecture as a way of increasing their delivery efficiency and runtime. However, you mustn’t be making these changes because other companies are making this move. Instead, have a firm grasp of the benefits of microservices architecture. They include:
Embracing automation and DevOps.
There’s a reduction in writing long, intricate lines of code.
Communication will improve among testing, QA, and development teams.
Finding and addressing bugs becomes quicker and easier.
Lightweight servers create faster startup times.
Independent scaling is available for each service.
See Problems Before Going Live
The cloud-native and microservices with DevOps means testing and production are integrated into the app lifecycle. Therefore, before going live, you can see problems by testing and troubleshooting. Organizations should keep in mind that, even though there is a multitude of benefits regarding microservice architectures, they’re not the ideal solution for all companies. The main reasons are they’re complex, require cultural changes, are expensive, and pose security challenges.
That doesn’t mean, however, microservice architectural frameworks doesn’t come with a set of benefits. For example, their design is such that they address the limitations found in monolithic architectures. Microservice architectures work toward modularizing an application into unique services to increase granularity.
Here are several benefits of using microservices architecture:
Companies can perform onboarding easier.
There’s less risk when microservices are implemented.
Microservices offer flexible storage for data.
Polyglot programming is enabled with microservices.
The reduction of clutter occurs.
There’s an increase in fault isolation and tolerance.
Companies experience an increase in the speed of deployment.
Scalability is available.
Security monitoring is simplified.
One of the most significant features of microservice architecture is that it’s scalable. You’ll find that it’s possible to scale each microservice independently. For example, if you need more power for one specific function, you can add it to the microservice providing that function. As demand changes, computing resources can automatically be increased or decreased as the changes in demand occur. As a result, it’s easier to maintain the infrastructure supporting your application.
It’s also possible to develop and deploy microservices independently. In doing so, development teams can focus on small, valuable features and deploy them. These deployments can occur without the fear of breaking down other parts of the application. Thanks to their small set of functionality, microservices are more robust and easier to test.
DevOps professionals know that every customer comes with a unique set of needs. Therefore, they commonly have configurations built in to meet those needs without separate applications deploying. Because microservices are separated and designed by functionality, it would be simple to toggle a feature on, allowing users to disable or enable particular microservices. When microservice architecture is designed correctly, it can be highly configurable without any worry of other parts of the application be affected.
CI Pipelines Will Become Obsolete
Currently, organizations and government entities are utilizing open source, and it’s the focus of their software development stacks. However, it wasn’t that long ago that open source was considered high-risk. With the recent acquisition of Red Hat from IBM and GitHub from Microsoft, which are homes of a variety of open source projects, this shows the general populace feels comfortable with open source. There will be increasing importance regarding DevOps and open-source practices. Specifically, DevOps teams will be using it in their Continuous Integration (CI) practices.
When you’re viewing a CI pipeline, it’s possible to see your app’s complete picture from its source control straight through to production. Now, CI isn’t your only priority. You also have to focus on CD (continuous delivery). What that means is, it’s time for your organization to invest its time and put effort into understanding how to automate your complete software development process. The main reason is that the future of DevOps is shifting away from CI pipelines and toward assembly lines.
What are CI Pipelines?
For those who don’t have a firm understanding of what a CI pipeline is, CI stands for Continuous Integration. Over the last few years, Continuous Integration has evolved tremendously. Initially, it launched as a system to automate the build and unit testing for each code; however, it’s evolved into a complex workflow. For example, the classic CI pipeline involved three steps, including build, test, and push. It’s evolved into other workflows, including CI pipelines that include forked stages, escalating, and notifications.
What are DevOps Assembly Lines?
DevOps Assembly Lines focus primarily on the automation and connection of activities several teams perform. These activities include CI for devs, config mgmt for Ops and infrastructure provisioning, deployments for multiple environments, test automation for Test, security patching for SecOps, and so on. Under most circumstances, an organization utilizes a suite of tools to automate specific DevOps activities. However, achieving CI is a challenging task because the DevOps toolchain is fragmented and difficult to glue back together.
Many teams adopt one of the following methods:
Gluing silos together using cultural collaboration.
Triggering one activity from another by writing ad-hoc scripts.
The second approach is better because it doesn’t introduce unnecessary human-dependancy steps or inefficiency. However, it only works well when working with one application using a small team.
Ultimately, DevOps teams solve this problem using Assembly Lines to address it by focusing on gluing together each activity into even-driven, streamlined workflows. These workflows can share state, as well as other information, easily across activities.
“There are significant benefits for companies to automate their software delivery process.” Manish Mathuria, CTO of Infostretch, explains, “advanced software development shops can put releases into production multiple times a day.”
What’s the Difference Between CI pipelines and Assembly Lines?
The CI pipeline features one activity in the entire Assembly Line. When breaking the project down into a chain of blocks, you can see a pipeline full of various activities. Each activity fulfills a specific need regarding configuration, notifications, runtime, tools integration, and so on. Different teams also own each pipeline, but they need to interact and exchange information with other pipelines.
Therefore, DevOps Assembly Lines are ultimately a pipeline created for pipelines. That means they must support:
Workflows across a variety of pipelines while quickly defining them.
Reusable and versioned workflows.
The ability to enable scaling for and rapid changes of microservices and (or) multiple applications.
Integrations with every source control system, artifact repository, DevOps tool, cloud, and so on.
Run-time to execute all pipelines.
Playbooks and Accelerators for standard tools and pipelines.
Manual approval gates or automatic triggers between all pipelines.
Serverless Technologies Will Provide Agility
One of the most significant problems DevOps teams had when working in earlier years is they worked separately in silos. These conditions led to a lack of transparency and poor teamwork. In many cases, DevOps teams need to merge, consolidate, and work together during the application’s lifecycle. Many times, this occurs right from development to deployment and throughout testing.
Delivering capabilities by leveraging functions as a service is the goal of DevOps professionals who have masters operating containerized workloads in complex ways. They’re achieving this goal by optimizing and streamlining this delivery. Throughout the next year, the depth and breadth on the focus of these functions will likely deepen. The main reason is that more professionals will recognize the benefits of working with serverless technologies as they become more comfortable leveraging containers in production.
“With the serverless approach it’s virtually impossible (or at least a bit pointless) to write any code without having at least considered how code will be executed and what other resources it requires to function,” writes Rafal Gancarz, “Serverless computing can be used to enable the holy grail of business agility – continuous deployment. With continuous deployment, any change merged into the code mainline gets automatically promoted to all environments, including production.”
Why Are Serverless Technologies Beneficial?
Some of the most significant ways serverless computing is providing benefits and agility to DevOps include:
better start-up times
improved resource utilization
However, despite these benefits, future DevOps professionals will become skilled at determining use cases whereby serverless computer and functions as a service are appropriate.
Agility and DevOps can work in conjunction with each other seamlessly without creating a hostile environment. The reality is the two working together create a holistic work environment by filling in the weaknesses each possess. In many workplaces, the future of DevOps is likely to compliment instead of supplanting Agile.
Creation of Modular Compartments
Often, Agile breaks down projects and creates modular and compartmentalized components. When there are more significant, organizational structures, this often leads to a lack of communication between teams and missed deadlines. Using DevOps deployment means internal structures of Agile teams that are kept in one place.
When thinking about the use of serverless computing, that doesn’t mean there aren’t any servers in use. Instead, machine resources are allocated by a cloud provider. However, the server management doesn’t have to be on the developer’s radar. That frees up time for focusing on building the best applications.
The cloud provider does everything else. When handling resource scaling, they make it automatic and flexible. Organizations are responsible for paying for only the resources they use, as well as when resources are used by applications. If organizations aren’t using resources, there’s no cost. Therefore, there’s no need for pre-provisioning or over-provisioning for storage or computing.
Serverless computing provides business agility because it makes it possible to create an environment whereby there are continuous developmental improvements. When organizations become agile enough for rapid decision-making, agility occurs and will lead them to success. Companies utilizing serverless computing to achieve DevOps will ultimately achieve greater agility.
Experience Changes Regarding IT
Organizations will also find that serverless computing doesn’t end with a path toward DevOps. It also leads to changes regarding IT, as well. For example, companies will be viewing the cloud differently. What that means is, because serverless computing relies heavily on the cloud, many long-standing IT roles will be redefined. Examples of these roles include architects, engineers, operations, and so on.
Traditional IT roles in a serverless computing world become less important. However, if that IT professional has a good working knowledge of the cloud and platforms, that becomes more important. That means this professional can accomplish more with the platform in comparison to a developer with expertise regarding their specialty, making it essential for organizations to have IT professionals who are skilled regarding the cloud.
The Future of DevOps: Conclusion
According to Grand View Research, “The global DevOps market size is expected to reach USD 12.85 billion by 2025.” These statistics demonstrate the rising adoption of cloud technologies, digitation of enterprises to automate business processes and soaring adoption of agile frameworks. These statistics also point out how, when IT teams improve, it enhances the efficiencies of operations.
The future of DevOps is something that can be seen as a cultural shift. It can also be seen as something that brings conventionally disconnected components in the development, deployment, and delivery of software into a single loop. Organizations are finding that DevOps is replacing their traditional IT departments. Not only are the titles changing, but the roles are changing, as well. Some of the roles have been eliminated, while others have been multiplied by the scale of microservice architectures.
The execution of successful DevOps relies on teams communicating clearly with each other. The future of DevOps means reduction of manual approvals, since automation is a huge part of the DevOps cycle.
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DevOps processes help companies to overcome the organizational challenges in an efficient, robust, and repeatable way. DevOps tools are a collection of complementary, task-specific tools that can be combined to automate processes. IronWorker and IronMQ are two DevOps tools from Iron.io that can help your business save money and scale on demand. Start your free 14 free Iron.i trial today!
The following solutions are some of the best DevOps tools that will ensure the creation and improvement of your products at a faster pace:
Source Control Management
GitHub is a web-based Git repository hosting service that offers all of the distributed revision control and source code management features as well as adding its own. Unlike Git, it provides a web-based graphical interface, desktop, and mobile integration.
GitLab, similar to GitHub, is a web-based Git repository manager with wiki and issue tracking features. Unlike GitHub, GitLab does not have an open-source version.
JFrog Artifactory is an enterprise-ready repository manager that supports software packages created by any language or technology. It supports secure, clustered, High Availability Docker registries.
More source control management tools are:
Database Lifecycle Management
DBmaestro offers Agile development and Continuous Integration and Delivery for the Database. It supports the streamlining of development process management and enforcing change policy practices.
Delphix is a software company that produces software for simplifying the building, testing, and upgrading of applications built on relational databases.
Flyway is an open-source database migration tool based around six basic commands: Migrate, Clean, Info, Validate, Baseline, and Repair. Migrations support SQL or Java.
More database lifecycle management tools are:
Continuous Integration (CI)
Bamboo is a continuous integration server that supports builds in any programming language using any build tool, including Ant, Maven, make, and any command-line tools.
Travis CI is an open-source continuous integration utility for building and testing projects hosted at GitHub.
Codeship is a continuous deployment tool focused on being an end-to-end solution for running tests and deploying apps. It supports Rails, Node, Python, PHP, Jaca, Scala, Groovy, and Clojure.
FitNesse is an automated testing solution for software. It supports acceptance testing rather than unit testing in that it facilitates a detailed readable description of system function.
Selenium is a software testing tool for web apps that offers a record/playback solution for writing tests without knowledge in a test scripting language.
JUnit is a unit testing tool for Java. It has been prominent in the development of test-driven development and is a family of unit testing frameworks.
Apache JMeter is an Apache load testing tool for analyzing and measuring the performance of various services, with a focus on web applications.
TestNG is a testing solution for Java inspired by JUnit. TestNG’s design aims to cover a broader range of test categories: unit, functional, end-to-end, integration, etc., with more easy-to-use functionalities.
More software testing tools are:
Ansible is an open-source software solution for configuring and managing computers. It offers multi-node software deployment, ad hoc task execution, and configuration management.
Puppet is an open-source configuration management solution for running on many Unix-like systems and Microsoft Windows. It also provides its declarative language to describe system configuration.
Salt platform is an open-source configuration management and remote execution application. It supports the “infrastructure-as-code” approach to deployment and cloud management.
Rudder is an open-source audit and configuration management tool that automates system configuration across large IT infrastructures.
More configuration tools are:
Terraform is a utility for building, combining, and launching infrastructure. It can create and compose all the components from physical servers to containers to SaaS products necessary to run applications.
AWS CodeDeploy is an automation tool for code deployments to any instance, including Amazon EC2 instances and instances running on-premises.
ElasticBox is an agile DevOps tool for defining, deploying and managing application automation agnostic of any infrastructure or cloud.
GoCD is an open-source automation tool for continuous delivery (CD). It automates the build-test-release process from code check-in to deployment. Various version control tools are available, including Git, Mercurial, and Subversion.
More deployment are:
Docker is an open-source product that makes it easier to create, deploy, and run applications in containers by providing a layer of abstraction and automation of operating-system-level virtualization on Linux.
Kubernetes is an open-source system for managing multiple hosts’ containerized applications, providing basic mechanisms for deployment, maintenance, and scaling of applications.
Apache Mesos is an open-source cluster manager that provides resource isolation and sharing across distributed applications or frameworks.
More container tools are:
OpenMake is a strategic software delivery utility that deploys to multi-platform servers, clouds, or containers. It simplifies component packaging, database updates, jumping versions, calendaring, and offloads your overworked CI process.
Plutora is an on-demand Enterprise IT Release Management software solution for building from the ground up to help companies deliver Releases that better serves businesses.
Spinnaker is an open-source multi-cloud continuous delivery platform for releasing software changes by enabling key features: cluster management and deployment management.
More release orchestration are:
Amazon Web Services (AWS) is a set of web services that Amazon offers as a cloud computing platform in 11 geographical regions across the world. The most prominent of these services are Amazon Elastic Compute Cloud and Amazon S3.
Microsoft Azure is a cloud computing platform for building, deploying, and managing applications and services through a global network of Microsoft-managed datacenters. It supports many different programming languages, tools, and frameworks, including both Microsoft-specific and third-party software and systems.
Google Cloud is a cloud computing solution by Google that offers to host on the same supporting infrastructure that Google uses internally for end-user products.
More cloud tools are:
Container Management Services
IronWorker is a tool that offers greater computing insights of tasks in real-time to optimize resource allocation and scheduling better. It tracks tasks with greater usage to understand the changing nature of organizations’ target audience and identify opportunities to streamline their compute.
AWS Fargate: is a serverless container management service (container as a service) that allows developers to focus on their application and not their infrastructure. While AWS Fargate does help with container orchestration, it does leave areas of concern where IronWorker fills the void, such as support, simplicity, and deployment options.
Google Cloud Run: is a managed platform that takes a Docker container image and runs it as a stateless, autoscaling HTTP service. The areas of concern where IronWorker fills the void are some key features, such as containerized environment, high-scale Processing, and flexible scheduling.
More container management tools are:
AI Ops Tools
Splunk enables searching, monitoring, and analyzing big data via a web-style interface. It can create graphs, reports, alerts, dashboards, and visualizations.
Moogsoft is an AIOps platform that helps organizations streamline incident resolution, prevent outages, and meet SLAs.
Logstash is a solution for managing events and logs. It enables collecting logs, parsing them, and storing them.
More AIOps tools are:
Datadog is an analytics and monitoring platform for IT infrastructure, operations, and development teams. It gets data from servers, databases, applications, tools, and services to give a centralized view of the applications in the cloud.
Elasticsearch is a search server that enables a distributed full-text search engine with a RESTful web interface and schema-free JSON documents.
Kibana is a data visualization plugin for Elasticsearch that provides visualization features on top of the Elasticsearch cluster’s content index.
More analytics tools are:
Nagios is an open-source solution for monitoring systems, networks, and infrastructure. It provides alerting services for servers, switches, applications, and services.
Zabbix is an open-source monitoring tool for networks and applications. It tracks the status of various network services, servers, and other network hardware.
Zenoss software builds real-time models of hybrid IT environments, providing performance insights that facilitate eliminating outages and reducing downtime, and IT spending.
More monitoring tools are:
SonarQube is a utility to manage code quality. It can cover new languages, adding rules engines, and advanced computing metrics through a robust extension mechanism. More than 50 plugins are available.
Tripwire is an open-source security and data integrity tool for monitoring and alerting on specific file change(s) on a range of systems.
Fortify reduces software risk by recognizing security vulnerabilities. It determines the root cause of the vulnerability, correlates, and prioritizes results, and provides best practices so developers can develop code more securely.
More security tools are:
Slack is a business communication tool that offers a set of features, including persistent chat rooms arranged by topic, private groups, etc.
Trello is a free project management utility that operates a freemium business model. Basic service is provided free of charge, though a Business Class paid-for service was launched in 2013.
JIRA is an issue tracking utility that offers bug and issue tracking, as well as project management functions.
More collaboration tools are:
Messaging queues tools
IronMQ: is an elastic message queue created specifically with the cloud in mind. It’s easy to use, runs on industrial-strength cloud infrastructure, and offers developers ready-to-use messaging with highly reliable delivery options and cloud-optimized performance.
AWS SQS: is a distributed message queuing solution offered by Amazon. It supports programmatic sending of messages via web service applications as a way to communicate over the Internet.
RabbitMQ: is an open-source message-broker solution for advanced message queuing with a plug-in for streaming text-oriented messaging protocol, MQ Telemetry Transport, and other protocols.
More messaging queues tools are:
Organizational transformations need some level of technological or tool-based assistance. DevOps, continuous integration, and continuous delivery are no distinctions. The tools organizations identify and use in pursuit of their goals are critical for their DevOps strategy’s success.
Iron.io offers two critical infrastructure DevOps tools in IronWorker and IronMQ. These tools will save your business money by allowing your teams to focus on application development and not waste time maintaining infrastructure. Start your free Iron.io trial today, and take your business to the next level. Please follow our blog for more articles on DevOps.
Evolution is the key to survival. This is not only true for living organisms but also for companies. DevOps is a set of tools and practices that help speed up the development and operationalization of software products. This allows companies to better serve their customers by providing them with high-quality products.
Essentially, this helps beat the competition. But beating your competitors isn’t the goal. The goal is to be better every time you intend to launch a new product. That’s where DevOps best practices come in. These practices focus on improving a set of factors which include:
Collaboration between the development and the operations team
DevOps best practices require continuous change. This means that your company will need to evolve and adopt an integrated change management strategy.
Here are some of the best DevOps practices:
1. Continuous Integration and Continuous Delivery
Continuous integration and continuous delivery (ci cd) involve the working together of both the development teams and the operations team. The developers in the development team should build codes and continuously merge them into a repository that they share with the operations team.
This allows the operations team to continuously test the code as it is being built. This makes it easy to identify any weaknesses in the code such as security defects. The collaboration between the two teams allows the process to have immediate feedback. Thus, making working together much easier. It also speeds up how fast the product will reach the market.
Continuous delivery builds upon continuous integration. This is because it creates production environments where automated builds are continuously tested and prepared for release. Proper implementation of the continuous delivery process ensures that a software release from your company has undergone a vigorous standardized process.
Automate every process in the product development and testing stage. Creating an automated system requires the use of technological tools. Some of the areas that will benefit from automation are code development, data, and network changes. The process of automation should also include creating test scenarios for new software development.
Creating automated test cases will help you know about various outcomes. This will help you find out which areas you can improve to have better software. Automate processes will help speed up the development cycle. This will give you a competitive edge over other players in the market. Effective automated testing requires the use of appropriate automation tools at each stage of the development process.
3. Use of Integrated Change Management
Technology is continuously changing and advancing with new innovative tools that make the current ones obsolete. Adopting continuous change management and integrating into both teams is key to meeting new customer demands especially under dynamic circumstances. Change management will help provide additional support by updating various processes of the development cycle.
Your company should adopt a flexible model that is open to change. This will make it easy to use integrated change management. You should also anticipate any significant technology changes and prepare all levels of your organization for adopting new practices.
4. Using Infrastructure as Code
Managing your infrastructure as code means using various software development techniques and continuous integration. This allows developers to use programs to interact with the company’s infrastructure. This process is also heavily reliant on automation. This is because developers can only use infrastructure as code when it comes to code-based tools.
Using infrastructure as code makes it easy to update the technology to the latest versions. It also improves the speed at which new products can get deployed to the market.
5. Monitor Existing Applications
Deploying the product shouldn’t be the last step. Proactively monitor the running applications. This will help you find new ways to optimize the existing product. Additionally, it will help you know what improvements will help similar products that haven’t reached the deployment stage. The monitoring process should be automatic and apps’ operating system can send various performance metrics back to the developers. Monitoring running applications will also provide you with data analytics on how to provide customer support.
6. Automated Dashboard
An automated dashboard gives the operations team with new insights that help them in the testing of new products. Developers’ operations can also leverage their intelligence with the automated dashboard. The dashboard also helps both teams get more in-depth information. This aids in developing new ways to make the product perform better.
The dashboard also makes it easier to review any configuration changes across the entire system. It also makes DevOps tooling more effective by giving the operations real-time data. Thus, you can analyze this data and select the best automation tools for various products.
7. Facilitate Active Participation of All Stakeholders
Working together is one of the key ways of delivering great products. Including the views of different stakeholders is key, even if they don’t participate in the product development cycle. DevOps team should consider the views and integrate some of their concerns or interests when possible. This may yield better results and involving stakeholders is key to building a great working environment.
8. Make the Automated Process Secure
A highly automated process needs very tight security. This is because cyber-attacks could result in massive losses of both crucial data and money. Use secure internal networks and grant access to only a handful of trustworthy individuals. Make security an important priority across the entire development cycle. Securing your processes will help you better manage product development.
9. Build Microservices Architecture
This is where you create one application by building several small services. The architecture should ensure that each small service is independent. This means that it can run alone and can communicate with other services. Each service should perform a specific purpose and should also work well with the different services.
10. Continuous Deployment
Make the deployment process continuous by releasing the product code in versions. This helps make the deployment process more efficient. It also makes testing the code much easier and allows the product to entire the final stage much more quickly. This helps minimize the risks of failure.
Thrive with DevOps
The collaboration between different teams in an organization is key to the overall success of the company. Implementing DevOps best practices ensures that both development and operation teams are on the same page in the product development process. This speeds up product development, minimizes risks, improves efficiency, and helps the company gain a competitive advantage over other players in the same industry. Start your free 14 day Iron.io trial and test out DevOps solutions such as IronWorker and IronMQ.
DevOps is a buzzword that sometimes means different things depending on who you ask. The actual definition of DevOps is a compound of development (Dev) and operations (Ops), DevOps is the union of people, process, and technology to continually provide value to customers.
DevOps teams from startups to large enterprise have been using Iron.io solutions to create awesome products for their customers. Get started today with a free 14 day Iron.io trial and test out IronWorker and IronMQ to your DevOps life cycle.
Here is a comprehensive guide to what DevOps is and what you need to know about its foundations and approach.
Why Was DevOps Created?
Created to meet the need to stay abrteast with throughput agile methods and increased software velocity, DevOps is a branch or offshoot of agile software development. Over the last decade, there became a need for a more natural approach to the end-to-end software delivery life cycle due to advancements in agile methods and culture.
In 2009, it was Patrick Debois who created the name and became a DevOps master. It is important to note that it is not a specific technology or process. Instead, it is more of a culture. For example, when discussing trends and adoption rates, it is considered a DevOps moment. Likewise, when an IT organization adopts it into their culture, this is called a DevOps environment.
With end-to-end solutions on Azure, teams can implement DevOps practices in each of the application life cycle phases: plan, develop, deliver, and operate. These DevOps technologies, combined with people and processes, enable teams to continually provide value to customers.
Teams that adopt DevOps culture, practices, and tools see their work evolve into being able to build their products faster and become more of a high-performance team. This creates a culture of better customer service. These benefits include:
Improving the mean time to recovery
Accelerating time to market
Maintaining system reliability and stability
Adapting to the competition and the market
There are four stages in the DevOps life cycle. These include its plan, develop, deliver, and operate phases.
In this phase of the life cycle, teams work on their ideas, define them, and describe the capabilities and features of the systems and applications being built. Teams track the progress at both high and low levels of granularity. These are anything from single-product task and beyond – including multiple products that span a variety of portfolios. DevOps teams track bugs, create backlogs, visualize their progress on dashboards, manage agile software development with Scrum, and use Kanban boards.
In this phase of the life cycle, this is the coding area. Things like writing code, testing it, and reviewing code, and integration are all part of the develop phase. Another aspect of the develop phase is building code into build artifacts. These can later be sent into a variety of environments. This allows the team to create at a fast pace without sacrificing stability, productivity, and most important – quality. The highly productive tools are used, as well as automating manual and mundane steps. They then reprise in small increases through continuous integration and automated testing.
Deploy applications to any Azure service, such as Kubernetes on Azure, automatically and with full control to maintain customer value. Spin and define numerous cloud environments such as HashiCorp Terraform or Azure Resource Manager. Then use Azure pipelines to deliver into environments featuring tools like Spinnaker or Jenkins or Azure Pipelines as part of the delivery process.
Gain insights from logs and telemetry, receive actionable alerts, and implement full stack monitoring with Azure Monitor. You can also manage the cloud environment with tools like Puppet, Chef, and Ansible or Azure Automation. Using Chef Automation or Azure Blueprints, keep all applications and provisional infrastructure in compliance. Easily minimize threat exposure, find vulnerabilities, and mediate them fast with Azure Security Center.
What is DevOps’ Goals?
The main goals of DevOps is to make collaboration better between all of the team. This is from the first stages of planning, all the way throughout automation and delivery. This does things like:
“High-performing IT organizations deploy 30x more frequently with 200x shorter lead times; they have 60x fewer failures and recover 168x faster.”
Recommended Reading: Best DevOps Tools
What Are the Phases of DevOps Maturity?
There are certain phases as part of DevOps Maturity which include the following:
In the past, development teams took three or four months to write code. After that, the codes were merged in order to release them. This process was tedious and difficult because the code would have different versions and many changes. This caused production issues that meant integration took much longer.
Continuous integration is combining the main body of code to be released with newly developed code.This sector saves much time when the team is ready for the code to be released.
Continuous deployment, not to be confused with continuous delivery [DevOps nirvana], is the most advanced evolution of continuous delivery. It’s the practice of deploying all the way into production without any human intervention.
Tools Used in DevOps
Source Code Repository
Unifying Enterprise Software Development and Delivery
For Future Reference
Learning about DevOps requires extensive research. And while no one article covers all of the bases, hopefully, this guide gives more insight into what it is all about and how it helps your team.
Iron.io has been helping DevOps teams by offloading tasks quickly and easily to Iron.io by using IronWorker and IronMQ. Give Iron.io a try with a free 14 day trial and see why DevOps teams around the world have found Iron.io a great tool for all phases of the DevOps life cycle.
AWS Fargate is a serverless container management service (container as a service) that allows developers to focus on their application and not their infrastructure. While AWS Fargate does help with container orchestration, it does leave areas of concern where IronWorker fills the void.
You should be paying less for your AWS Fargate workloads. Workload efficient enterprises are leaving Fargate for IronWorker. Speak to us to talk about why.
What are containers?
Before we talk about AWS Fargate, let’s talk about making software and containers. Making software applications behave predictably on different computers is one of the biggest challenges for developers. Software may need to run in multiple environments: development, testing, staging, and production. Differences in these environments can cause unexpected behavior, yet be very hard to track down.
To solve these challenges, more and more developers are using a technology called containers. Each container encapsulates an entire runtime environment. This includes the application itself, as well as the dependencies, libraries, frameworks, and configuration files that it needs to run.
Docker and Kubernetes were two of the first container technologies, but they are by no means the only alternatives. These containers are then used in container management services. For example, IronWorker, Iron.io’s container management service, uses Docker containers.
What is AWS Fargate?
Amazon’s first entry into the container market was Amazon Elastic Container Service (ECS). While many customers saw value in ECS, this solution often required a great deal of tedious manual configuration and oversight. For example, some containers may have to work together despite needing entirely different resources.
Performing all this management is the bane of many developers and IT staff. It requires a great deal of resources and effort, and it takes time away from what’s most important: deploying applications.
In order to solve these problems, Amazon has introduced AWS Fargate. According to Amazon, Fargate is “a compute engine for Amazon ECS that allows you to run containers without having to manage servers or clusters.”
Fargate separates the task of running containers from the task of managing the underlying infrastructure. Users can simply specify the resources that each container requires, and Fargate will handle the rest. For example, there’s no need to select the right server type, or fiddle with complicated multi-layered access rules.
AWS Fargate vs ECS vs EKS
Besides Fargate, Amazon’s other cloud computing offerings are ECS and EKS (Elastic Container Service for Kubernetes). ECS and EKS are largely for users of Docker and Kubernetes, respectively, who don’t mind doing the “grunt work” of manual configuration aka container orchestration.
One advantage of Fargate is that you don’t have to start out using it as an AWS customer. Instead, you can begin with ECS or EKS and then migrate to Fargate if you decide that it’s a better fit.
In particular, Fargate is a good choice if you find that you’re leaving a lot of compute power or memory on the table. Unlike ECS and EKS, Fargate only charges you for the CPU and memory that you actually use.
AWS Fargate: Pros and Cons
AWS Fargate is an exciting technology, but does it really live up to the hype? Below, we’ll discuss some of the advantages and disadvantages of using AWS Fargate.
Lower Costs (Maybe)
Higher Costs (Maybe)
Pro: Less Complexity
These days, tech companies are offering everything “as a service,” taking the complexity out of users’ hands. There’s software as a service (SaaS), infrastructure as a service (IaaS), platform as a service (PaaS), and dozens of other buzzwords.
In this vein, Fargate is a Container as a Service (CaaS) technology. You don’t have to worry about where you’ll deploy your containers, or how you’ll manage and scale them. Instead, you can focus on defining the right parameters for your containers (e.g. compute, storage, and networking) for a successful deployment.
Pro: Better Security
Due to their complexity, Amazon ECS and EKS present a few security concerns. Having multiple layers of tasks and containers in your stack means that you need to handle security for each one.
With Fargate, however, the security of your IT infrastructure is no longer your concern. Instead, you embed security within the container itself. You can also combine Fargate with container security companies such as Twistlock. These companies offer products for guarding against attacks on running applications in Fargate.
Pro: Lower Costs (Maybe)
If you’re migrating from Amazon ECS or EKS, then Fargate could be a cheaper alternative. This is for two main reasons:
As mentioned above, Fargate charges you only when your container workloads are running inside the underlying virtual machine. It does not charge you for the total time that the VM instance is running.
Fargate does a good job at task scheduling, making it easier to start and stop containers at a specific time.
Of course, the downside of Fargate is that you sacrifice customization options for ease of use. As a result, Fargate is not well-suited for users who need greater control over their containers. These users may have special requirements for governance, risk management, and compliance that require fine-tuned control over their IT infrastructure.
Con: Higher Costs (Maybe)
Sure, Fargate is a cost-saving opportunity in the right situation when switching from ECS or EKS. For simpler use cases, however, Fargate may actually end up being more expensive. Amazon charges Fargate users a higher per-hour fee than ECS and EKS users. This is to compensate for the complexity of managing your containers’ infrastructure.
In addition, running your container workloads in the cloud will likely be more expensive than operating your own infrastructure on-premises. What you gain in ease of use, you lose in flexibility and performance.
Con: Regional Availability
AWS Fargate is slowly rolling out across Amazon’s cloud data centers, but it’s not yet available in all regions. As of June 2020, Fargate is not available for the following Amazon regions:
AWS Fargate (EKS)
GovCloud (US-West and US-East)
* = Includes AWS Fargate (ECS)
AWS Fargate Reviews
Even though AWS Fargate is still a new technology, it has earned mostly positive feedback on the tech review platform G2 Crowd. As of this writing, AWS Fargate has received an average score of 4.5 out of 5 stars from 12 G2 Crowd users.
Multiple users praise AWS Fargate’s ease of use. One customer says that Fargate “made the job of deploying and maintaining containers very easy.” A second customer praises Fargate’s user interface, calling it “simple and very easy to navigate.”
Another reviewer calls AWS Fargate an excellent solution: “I have been working with AWS Fargate for 1 or 2 years, and as a cloud architect it’s a boon for me… It becomes so easy to scale up and scale down dynamically when you’re using AWS Fargate.”
Despite these advantages, AWS Fargate customers do have some complaints:
One user wishes that the learning curve were easier, writing that “it requires some amount of experience on Amazon EC2 and knowledge of some services.”
Multiple users mention that the cost of AWS Fargate is too high for them: “AWS Fargate is costlier when compared with other services”; “the pricing isn’t great and didn’t fit our startup’s needs.”
Finally, another user has issues with Amazon’s support: “as it’s a new product introduced in 2017, the quality of support is not so good.”
AWS Fargate Alternatives: AWS Fargate vs Iron.io
While AWS offers Fargate as a serverless container platform running on Docker, Iron.io offers an alternative industry leading solution called IronWorker.IronWorker is a container-based platform with Docker support for performing work on-demand. Just like AWS Fargate, IronWorker takes care of all the messy questions about servers and scaling. All you have to do on your end is develop applications, and then queue up tasks for processing.
Why select IronWorker over AWS Fargate?
IronWorker has been helping customers grow their business since 2015. Even with IronWorker’s AWS Fargate’s similarities, IronWorker has the advantage in:
We understand every application and project is different. Luckily, Iron.io offers a “white glove” approach by developing custom configurations to get your tasks up and running. No project is too big, so please contact our development team to get your project started. We also understand that documentation is critical to any developer and have made a Dev Center to help answer your questions.
When you start your free 14 day trial, you will get to interact with the simple and easy to use Iron.io dashboard. Once you have your project running, you will receive detailed analytics providing both a high level synopsis and granular metrics.
As of June 2020, Fargate’s container scaling technology is not available for on-premises deployments. On the other hand, one of the main goals of Iron.io is for the platform to run anywhere. Iron.io offers a variety of deployment options to fit every company’s needs:
Users can run containers on Iron.io’s shared cloud infrastructure.
Users benefit from a hybrid cloud and on-premises solution. Containers run on in-house hardware, while Iron.io handles concerns such as scheduling and authentication. This is a smart choice for organizations who already have their own server infrastructure, or who have concerns about data security in the cloud.
Users can run containers on Iron.io’s dedicated server hardware, making their applications more consistent and reliable. With Iron.io’s automatic scaling technology, users don’t have to worry about manually increasing or decreasing their usage.
Finally, users can run IronWorker on their own in-house IT infrastructure. This is the best choice for customers who have strict regulations for compliance and security. Users in finance, healthcare, and government may all need to run containers on-premises.
Like it or now, AWS Fargate is a leader in serverless container managment services. As we’ve discussed in this article, however, it’s certainly not the right choice for every company. It’s true that Fargate often provides extra time and convenience. However, Fargate users will also sacrifice control and incur potentially higher costs.
As alternative to AWS Fargate, IronWorker has proven itself an enterprise solution for companies such as Hotel Tonight, Bleacher Report and Untappd. IronWorker, made by Iron.io, offers a mature, feature-rich alternative to Fargate, ECS and EKS. Users can run containers on-premises, in the cloud, or benefit from a hybrid solution. Like Fargate, IronWorker takes care of infrastructure questions such as servers, scaling, setup, and maintenance. This gives your developers more time to spend on deploying code and creating value for your organization.
Every web application needs to handle background jobs. A “background job” is a process that runs behind the scenes. Great effort goes into making web page response as fast as possible, which means getting data to the screen, completing the request, and returning control to the user. Background jobs are created to handle tasks that take time to complete or that aren’t critical to displaying results on the screen.
For example, if a query might take longer than a second, developers will want to consider running it in the background so that the web app can respond quickly and free itself up to respond to other requests. If needed, the background job can call back to the webpage when the task has been completed.
Why are container based background jobs important to developers?
Many things that rely on external services are also suited for running as background jobs. Sending an email as confirmation, storing a photo, creating a thumbnail, or posting to social media services are jobs that don’t need to be run in the front as part of the web page response. The controller in the application can put the email job, image processing, or social media posts into a jobs queue and then return control to a user. Jobs that run on a schedule are also considered background tasks.
Do container based background jobs help companies scale?
As your application grows, your background jobs system needs to scale which makes it a perfect match for Iron.io’s services. IronWorker facilitates background job processing with the help of docker containers. Containers have become part of the infrastructure running just about everything. Almost everyone has their version of containers. The most commonly used is still Docker. IronWorker was among the very first to combine serverless management with containers.
Forgetting about managing a server to react to spikes in traffic or other processing needs greatly simplifies a developer’s job. Tasks and other processes are scaled automatically. At the same time this allows for detailed analytics. Because the containers are managed by IronWorker, whether they are short lived or take days, the jobs are completed with minimal developer input after the initial setup.
What is a SaaS company that provides a simple easy-to-use application to offload container based background jobs?
IronWorker provided by Iron.io is the answer. Start running your background jobs using IronWorker today with a free 14 day trial.
A very common use case for using a service like Ringcaptcha is to be able to schedule SMS’s or calls. Maybe you want to schedule a text to go out at specific time, or notify all your users about something via SMS every day. Ringcaptcha doesn’t have scheduling built in, but here’s an easy way to schedule your Ringcaptcha SMS’s using IronWorker.
All of the code in this post is available on Github and I recommend you clone that repo as a starting point. You will need to have an Iron.io account and a Ringcaptcha account to run the examples and this post is meant to quickly take you through the important things without going into setup/configuration which you can find on this README.
Create an SMS worker
First, let’s start by creating a simple sms worker. You can write this in any language, but for this post, I’ll be using Ruby. This worker simply sends an SMS via the Ringcaptcha API, but you can easily make it do a whole lot more like get data from various places and send a more meaningful message depending on what your application does. This is sms.rb:
Upload the worker
Now that we have our worker code, we need to install our worker’s dependencies, zip the code and upload to Iron. Pull our github repo and run the following commands:
docker run --rm -v "$PWD":/worker -w /worker iron/ruby:2.4-dev bundle install --standalone --clean
zip -r ringcaptcha-worker.zip .
iron worker upload -e "APP_KEY=YOUR_RINGCAPTCHA_APP_KEY" -e "API_KEY=YOUR_RINGCAPTCHA_API_KEY" --name ringcaptcha-worker --zip ringcaptcha-worker.zip iron/ruby:2.4 ruby sms.rb
Queue up tasks for the worker
Now that we’ve created our sms worker and uploaded it, we can queue up tasks for it. One task or millions of tasks, doesn’t matter.
iron worker queue --payload-file payload.json --wait ringcaptcha-worker
Sending notifications is key to delivering great service. A growing user base means distributing the effort and shrinking the time it takes to get emails and messages to your users.
Sending notifications is a required part of almost any application or service. Whether it’s sending verification emails, texting users, sending out a newsletter, emailing usage data, or even a more complicated use case, it’s important for you to keep in communication with your users.
This communication never really needs to block requests, however. Notifications are asynchronous by nature, which makes them a perfect match for Iron.io’s services. As your application grows, your notification system needs to scale with your user base and usage. This, again, is something that the elastic, on-demand, massively scalable Iron.io architecture supports out of the box.
Notification workers generally follow the same three-step process:
Create Your Workers. Create different workers to handle a variety of emails and notifications—alerts, daily summaries, weekly updates, personalized offers, special notices, and more.
Choose Your Delivery Gateway. Use an SMTP gateway like SendGrid or an API like Ringcaptcha to manage the actual sending, monitoring, and analysis of the delivery step.
Process and Send Notifications in Parallel. Use IronWorker to handle the processing and interface with the gateway. Queue up thousands of jobs at once or use scheduled jobs to send messages at set times.
The worker can also be split up into three major steps: initializing the notification headers, preparing and sending the notification, and signaling exceptions and recording the status.
For a detailed example using SendGrid, IronWorker, and Ringcaptcha, check out our docs.
Preparing the Headers
Based on your gateway, your language, and your library, this step may be trivial. It consists largely of configuring the sender, the subject, and other information that is common to all the notifications.
Preparing the Notification
This will again depend on your specific implementation, but this will almost always consist of a loop through the users you want to notify. If the notifications are customized on a per-user basis, this is when the message would be generated. Finally, the worker sends the mail or notification.
Signaling Exceptions & Recording Status
This step is an important one if stability and logging are important to your notifications. “Signaling Exceptions” simply means notifying your application when something goes wrong–this can be as simple as a callback to an HTTP request endpoint, pushing a message to IronMQ, or flagging a notification in the database. However you want to do it, you should implement a way to trigger retries on notifications. Scheduled workers can help in this: simply schedule a worker to run every hour or every day and retry emails or notifications that threw errors or failed. If a messge fails a certain number of times, bring it to the attention of your team, as it probably indicates a bug in your worker.
Recording status is important for providing an audit log. It’s often important to know that, e.g., the user was warned about their overdue status. You should log that the notification or email was successfully sent, along with the timestamp.
Sending in Parallel
Notifications and emails can often need to be sent in a timely fashion; users are often not impressed with 9 hour delays between an event and receiving a notification of it. As your usage and user base grow, a single task that processes notifications one at a time will quickly become inadequate.
The solution to this lies in massive parallelisation. By queuing tens, hundreds, or thousands of tasks to manage your queue, you can process a staggering amount of notifications and emails in a brief time period. Many hands makes light work.
Workers do have a setup time, and sending a notification is a pretty quick action. To try to make the most of the setup time, we usually recommend that tasks run for at least several minutes. The most straight-forward architecture, queuing a task for each notification, will work—it’s just not the most efficient method available. A more elegant model would be to batch notifications into tens or hundreds, then queue that batch, instead of all tasks or just one.
Using IronMQ to Guarantee Delivery
IronMQ uses a get-delete paradigm that keeps messages on the queue until they are explicitly deleted, but reserves them for short periods of time for clients to prevent duplicate handling. This architecture makes it really easy to implement messages that will automatically retry. As long as a message is not removed from the queue until after the worker sends it, any error that causes the worker to fail or sending to fail will result in the message being returned to the queue to be tried again, without any intervention or error-handling on your part.
Furthermore, IronMQ can be used for tightly controlled parallelisation. Assuming messages are queued up, workers can be spun up to consume the queue until it is empty. This allows you to spin up as many workers as you want, working in parallel with no modification to your code or batching. You can avoid overloading an API or database with thousands of simultaneous requests through this tight control over the number of running workers.
For example, the following ruby code sends SMS using Ringcaptcha:
You can find more details and other code samples on github.