22 billion records! Thanks to the security breaches, that’s the amount of data exposed to the crackers (hackers who are bad guys) in 2021 alone. Healthcare, finance, education, retail, eCommerce, defense… you name the industry — they are all vulnerable to cyber threats. Fast forward to 2023, organizations acknowledge the growing need for continuous and fast application delivery. They also understand the importance of embracing SDLC practices like DevOps to prioritize the security, agility, and reliability of the products they build. Also, imbibing DevOps culture into your organization helps reduce magnanimous CAPEX & OPEX associated with server & network infrastructure management.
Read this insight to understand DevOps — in and out.
A Little Backdrop to Up the DevOps Ante
In 2023, to stay relevant, companies, big and small alike, are committing to building more secure & efficient IT infrastructure. And the commitment is not all just for brand positioning.
The revolution is happening!
- 83% of IT decision-makers report implementing DevOps practices for better organizational performance.
- Not just that, the DevOps ecosystem i.e., the DevOps tools & services market is estimated to be growing at a CAGR of 24.2% and would be worth as much as $57.90 billion by 2030.
Aren’t these figures aptly underlining the rise and rise of DevOps, which is predicted to be continued over the next decade? But it’s worth questioning whether it’s all smoke or there is an actual fire.
We do understand that your headspace, right now, might be a complete hotchpotch with questions flooding in from all directions — from every single neuron in there:
- What’s DevOps?
- What’s DevSecOps?
- What’s the buzz around platform engineering?
- Is DevOps already on its deathbed? Is it too late to implement DevOps in 2023?
- What are DORA metrics?
- Do I even need DevOps in the first place?
Rest assured, we shall answer them all.
What Is DevOps?
Is DevOps a technology? Nope. DevOps is not a technology per se. It’s an umbrella term for a set of practices and approaches to software engineering.
DevOps is a people & culture-first approach to software development that interweaves SDLC tools, processes, & IT operations together.
In a non-cryptic lingo, DevOps practices help you integrate your development tools, technologies, and processes in a way that automates & streamlines your SDLC processes, facilitates efficient collaboration among your software teams, and enables them to ship features on-demand i.e., continuous delivery of software.
So, when DevOps engineers are not taking power naps on the office couch, or when they are not busy changing their video backgrounds in Zoom/Teams/Gmeet, you’ll find them playing with version control systems, automation tools (hey CI/CD), monitoring tools, containerization platforms, cloud computing, and what not to enable the rapid and reliable delivery of software.
In general, DevOps is meant to yield the following outcomes for engineering teams—
- increase deployment frequency
- Shorten the time to market
- Minimize the failure rate of new releases
- Quicken the bug fixes and shorten lead time to change (LTTC)
- Improve mean time to recovery (MTTR)
DevOps is omnipresent. It’s the way modern software is being developed. It’s so integral to software development today that new engineers when they hear from their engineering manager that “we would be implementing DevOps for this project”, are often in shock with furrowed brows and jaws wide open. They wonder “what do you mean? Isn’t that the de-facto way to software development? Huh?”.
But a small bunch of organizations are still in the legacy days and are yet to modernize their infrastructure. Here we list three reasons why you should be considering DevOps.
#1- Avoid crisis
When you ship the code, and it works… don’t you feel as exhilarated as Jack? You may even sometimes feel like squealing and shouting “I’m king of the world”.
Nothing wrong with that.
But when the iceberg hits, wouldn’t you also want a proper crisis-management plan in place to avoid the Titanic’s fate?
That’s what DevOps gives you — the assurance. But not everyone takes a security-&-safety-first approach to software development. Knight Capital had to pay the price of slacking on not implementing DevOps the right way. Result? An empire that was built in 17 years was down to debris in an hour.
They lost $440 Mn+ in one hour because of bad engineering practices — manual deployments, inefficient code refactoring, improper code review, lack of automated systems to alert the team about discrepancies, and no procedures in place to roll back to the previous versions of properly functional working software or halt the system to minimize the losses. Read about it here. Amazon too had a sad incident where it led to $160Mn+ in losses.
Implementing DevOps doesn’t guarantee 100% safety from such incidents, but it’s the best you’ve got to avoid crises as far as possible and respond to them lightning-fast.
#2- On-Demand/Continuous Software Delivery & Improved DORA Performance
The Telegraph, one of the most popular print & digital news publishers, reported a 25% YoY increase in the number of releases, and a 7% decrease in failure rates when they adopted DevOps. They aimed to be a faster, better, and ever-growing organization.
[Read more: How to use DORA metrics for software delivery]
#3- Reduced OpEx And CapEx
On-premise server assets & network infrastructure costs a premium. As DevOps encourages to use of cloud infrastructure, often, it helps organizations to save money by cutting operational & capital expenditures associated with on-premise infrastructure. This buys more time for engineers and management to channel resources toward improving the quality of software & its delivery.
This must be getting repetitive. But DevOps puts a lot on your plate to help you deliver awesome software products. Because it has its root in Agile, Lean, Kaizen, and other software methodologies — the benefits are overlapping too.
Speed of Delivery
The foremost benefit of DevOps is the ability to operate at high velocity, which allows teams to rapidly innovate and adapt to changing markets. Thanks to microservices (loosely-coupled software/services architecture) and continuous delivery (automated software version control, build, testing, and delivery pipeline) technologies, developers and operations teams are equipped to take ownership of services and release updates with ease, and at scale.
Accuracy of Delivery
Users doesn’t hug applications with bugs. Okay, that rhyme is not amusing at all, LoL. Anyway, the point is nobody adores bugs. 62% of users uninstall a mobile app because either it crashes or there is some sort of glitches in it. DevOps teams understand this, and practicing DevOps principles enables them to rapidly respond to discovered/reported bugs and fix them based on priority. This, in turn, leads to stable builds, improved customer satisfaction, and a positive user experience.
Infrastructure as code is one of the core DevOps practices — a programmatic approach, which makes it easy to launch, configure, provision, and manage servers, databases, and infrastructure in general. Administrators no longer have to manually set up and configure servers, or update versions and patches. Everything is programmatic, and only if an error happens, which is not handled by code then human administrators need to intervene. As everything is programmatically done, thousands of servers can easily be monitored and managed in parallel. This makes DevOps-led software companies highly scalable and empowers them to smoothly & efficiently work with complex or changing systems, not to mention, with reduced risk.
DevOps, as mentioned earlier, is not a technology. It’s an amalgamation of people, processes, technical tools, and engineering practices. To put it right, it’s a cultural shift in how tech is done in organizations. A crucial aspect of any tech organization’s success is how well its engineering people & teams collaborate internally, and with external teams. DevOps advocates high ownership and accountability among individuals & teams. In DevOps culture, development and operations teams work closely together, share responsibilities, and combine their workflows, which reduces inefficiencies and saves time.
Security & Compliance
DevOps approach uses policy as code (automated compliance policies), and infrastructure as code principles. These ensure that security and compliance are maintained while still allowing for quick and efficient development.
In summary, DevOps solves pain points related to velocity, reliability, scalability, collaboration and security in modern software development lifecycles. By utilizing the various tools and practices associated with DevOps, teams can stay ahead of the competition and provide a high-quality experience for end-users while still maintaining a strong focus on security and compliance.
The Bumpy Road to Adopting DevOps
DevOps is a cultural shift to delivering solutions. In a traditional setup, if a code performs its intended functionality in a production-like environment, that’s where the developer’s job is done.
Now, if the same code crashes in the actual production environment, it’s on the operations team to take care of it.
The roles & responsibilities, the team structure, and the department in a traditional IT company are all siloed. This adds extra processes to the SDLC — code handover, and knowledge transfer. AND If you’ve ever coded, you would know how painful it is to debug someone else’s code, LoL.
DevOps fixes this challenge arising from siloed processes by fusing both Dev & Ops together. In DevOps, delivering working code ain’t just a developer’s job, Ops guys are equally invested in the development & testing. Similarly, developers are equally responsible for ensuring that delivered code works in a production environment. It fosters accountability & ownership across the teams.But is it as simple as it sounds?
No, it’s not a cakewalk.
The road to DevOps adoption is full of bumps and potholes. Here are some bottlenecks & challenges associated with DevOps adoption—
- Resistance to move from siloed organizational structure
- Shifting from legacy to decoupled microservices & serverless computing introduces overwhelming operational workload. Often teams are not trained to shoulder this.
- Over-reliance on tools can keep the teams away from truly embracing DevOps and may not unlock true tangible value for them.
[Read more: 5 DevOps best practices for engineering teams]
How to Adopt & Implement DevOps?
Here a few ways through which engineering teams can adopt, implement, and sustain DevOps:
- Understand that DevOps is first about people & culture, then about process & practices, and lastly about tech & tools, and automation.
- Educate everyone in a DevOps team about the entire value stream — from software ideation to design, UX, development, testing, delivery, deployment, CX, and maintenance.
- Invest in building robust foundations of automation, configuration management, and continuous delivery principles.
- Invest equally in training teams for effective communication and collaboration.
- Modern infrastructures: Remove any barriers to DevOps adoption — don’t burden the teams by forcing them to use your existing infrastructure. Allow them to devise their own architectures, tools, tech stack, and infrastructure.
- Autonomous teams: The more you decrease the reliance of your DevOps teams on external teams for building, deploying, and managing products, the more effective will be DevOps implementation.
- Cross-functional, multidisciplinary teams take the driving seat to align people, processes, and tools for delivering solutions that delight customers. Effective communication & collaboration are in the DNA of DevOps teams.
Encourage Continuous Learning
- Risk-averse organizations perform poorly on DevOps metrics. 33% of low-performing DevOps teams quote risk aversion as a growth impediment.
- Encourage your engineers toward experimentation, bold innovation, and continuous learning. Continuous improvement of SDLC workflows can’t be imagined without experimentation.
- DevOps can be easily embraced, and drive amazing results, by truly agile teams.
- Many DevOps principles are the same as that of Agile — including the first principle in the agile manifesto i.e., “satisfy the customer through early and continuous delivery of valuable software.
- Read our insight on Agile SDLC.
DevOps Practices, And Principles
DevOps practices are targeted at:
- Streamlining SDLC processes & infrastructure management
- Incremental & frequent updates for minimal & manageable bug risks
- Microservices powered flexible IT architecture
- Automation & CI/CD led rapid innovation
- Continuous monitoring & logging for building resilient & reliable software
Continuous Integration (CI)
CI is the process of frequently integrating new code into an existing central repository using Git or any version control system. With CI, every code merge triggers automated builds and tests, if there are any conflicts, bugs, or errors, then they are identified early in the delivery process and handled/fixed based on how critical it is.
Continuous Integration (CD)
An expansion of the CI principle, where the builds are pushed to the testing environment(s), aka a production-like environment. Next, they are subjected to rigorous unit testing, UI testing, performance testing, API reliability testing, and integration testing, among several others. If any issues surface, they can be handled properly. Else, you’ll have a ready-to-be-deployed build artifact for your software.
It’s a software architecture design pattern where a large piece of software is built and deployed as multiple small & independent components. Taking the example of eCommerce, think of this as your product catalog as one microservice, your cart as another microservices, your package tracking system as a separate microservice, and similarly for a user account, and payments. Now, all these standalone components (which cater to specific business functions) of an e-commerce system communicate with each other using APIs (consider it as accessing a URL with certain parameters).
This makes software infinitely scalable, as you can independently build any new feature and integrate it into the core. The same goes for dropping a feature off the platform. Anyway, microservices help unlock greater flexibility and build resilient software as by design it facilitates fault isolation. But again, it is not a cakewalk. You need to be wary of operational complexity while implementing microservices i.e., service boundaries (logical & physical separation of individual components in a microservices architecture), data consistency (for API communications), and security.
Infrastructure as Code (IaC), configuration management, and policy as code
What microservices is for functional components of your application, IaC is the same for your infrastructure and environments (mostly in the cloud). Infrastructure as Code is a programmatic DevOps practice that automates spinning testing & production environments in the cloud (hello, Containers & Kubernetes) or on-premise.
In simple terms, if you need an nginx server on your Ubuntu machine, and need to install a certain Database, configure network firewalls, and other stuff that usually operations teams perform — infrastructure configuration management — then all of it can be automated by writing code that does the same every single time for you.
How CI/CD automates build & testing using code, the same way IaC automates the creation & termination of computing resources and infrastructure environments.
The Cherry on the cake, it’s not only the infrastructure and its configuration that can be codified. You can also dynamically govern/monitor/track changes in your infrastructure and environment at scale by enforcing code-led compliance (policy as code).
IaC DevOps practices impart automation-powered agility & resilience to your IT projects.
Monitoring & Logging
Once your infrastructure and application code are in action, continuous monitoring, logging, analysis, alert, and optimization needs to be performed to ensure smooth operations. For this too, you can use automation.
Usually, you need to track latency (performance), traffic (load), error (health), and saturation (usage) metrics of your infrastructure (CPU, memory, storage, applications & services, servers & communication networks, external dependencies & environments).
The monitoring & logging principle includes — data collection & logging, data monitoring through visualization dashboards and code analysis, auto response to expected conditions, auto ensure compliance and security.
Communication & Collaboration
A core differentiator among successful DevOps culture-led organizations is interoperability among different teams and departments. Teams who cultivate a culture of effective communication & collaboration using an agile approach like regular sprint & feedback-loop, or those who facilitate information sharing by use of chat applications, group communications, project tracking, performance tracking, project wikis, etcetera tend to outperform those who don’t.
Though, the number of DevOps SDLC stages may vary based on specific organizational practices, and SDLC frameworks being used, they all have testing, security, and compliance embedded in the entire DevOps lifecycle stages. On a high level, the iterative DevOps lifecycle stages boil down to the following—
Planning i.e., Ideation
Customer-focused approach to brainstorming new features, aka ‘backlog’, and functionalities to be included in upcoming development cycles for optimizing the customer experience, and maximizing business KPIs.
Transforming backlog (new features) documents into code using test-driven development, pair programming, functional programming, code reviews, and other coding paradigms.
Continuous Integration & Continuous Delivery (CI/CD)
Merge the code developed in the last stage to the existing repository, preferably a test environment, aka a production-like environment. Run tests, debug it, check for compliance, and build the ready-to-be-deployed package.
Deployment (or continuous deployment)
If the runtime build from CI/CD pipelines meets all the quality, compliance, and security expectations/requirements, the build is ready to be deployed in production. Ideally, a good DevOps practice is to deploy builds dynamically. This is because even after extensive testing, we can’t completely guarantee a bug-free deployment. So, when the build is deployed to a subset of real-world users, DevOps teams can collect and analyze the usage metrics to identify any potential errors or defects, and they may respond to it before releasing it to all users.
Monitoring & maintenance
The moment the build is deployed to production, it’s action time for the DevOps teams to monitor the performance, availability, and overall experience of both the infrastructure and the application. If there are any red flags, immediately the concerned teams should be notified.
Continuous Learning & improvement
Lastly, it is all about listening to the end customers. Loop in their feedback and requests into the next planning phase, and iteratively & incrementally keep shipping awesome features back to the users.
DevOps tools are supposed to facilitate asynchronous collaboration among individuals & teams, and integrate workflows. Here are some DevOps tools which you may use to unlock higher performance for your DevOps teams—
Project management tools — for project planning, team formation, responsibility & resource allocation, and effective communication & collaboration. Ex, Jira, Kanban boards, Slack, MS Teams, etcetera.
Source-code version control system & collaborative repositories — for managing multiple versions of the same project, and for facilitating collaborative coding. Also, these tools should enable easy code integration to CI/CD pipelines. Ex, Gitlab, Github, etcetera.
CI/CD pipeline tools — Platforms like CircleCI, Jenkins, and GitLab that give you ready-to-use managed infrastructure to automate code builds, run tests, and enforce compliance.
[Read more: Top CI/CD pipeline tools for 2023]
Test automation frameworks/platform — Tools that allow you to test your code/builds and run them through unit, functional, integration, performance, penetration, and security testing. Selenium, Appium, Cucumber, LambdaTest, and Browserstack are popular test automation frameworks & platforms.
Cloud platforms — AWS, Azure, and GCP are popular platforms to host your applications in the cloud and provide a suite of infrastructure management tools.
Infrastructure & Configuration tools — These enable you to automate the launching, provisioning, and monitoring of your application infrastructure. Ansible, Terraform, Kubernetes, Chef, and Puppet are wildly popular for infrastructure configuration.
Monitoring tools — Datadog, Splunk, and some other tools help you monitor your DevOps infrastructure and its performance metrics.
Continuous feedback tools — Tools like HotJar and Google analytics to gain insights into how customers are interacting with your application.
Engineering analytics tools — These help you gain insights into your engineering performance, and help you track and analyze DevOps performance i.e., DORA metrics. We, Hatica, are a go-to platform for engineering managers to track and optimize the overall performance of their engineering teams.
DevOps Performance Metrics
Google’s DevOps Research & Assessment team has identified four key metrics against which you can benchmark your DevOps processes to assess your performance and identify opportunities for optimization. The key metrics are —
- Deployment Frequency
- Change Lead Time
- Change Failure Rate
- Mean Time To Restore
We’ve discussed these in detail in our insight on metrics to monitor for architecting highly successful DevOps organizations. Feel free to read it and share it with your engineering peers.
[Read more: A-Z Guide to DORA Metrics]
DevSecOps is how ideally the DevOps should be i.e., security embedded into every stage of the DevOps lifecycle. Like how we have testing integrated into all stages from development to deployment, the same way, DevSecOps is security injected into DevOps stages — from planning to development, delivery, deployment, and maintenance.
But most organizations are not experienced with security-led software development, posing a cultural challenge to DevSecOps adoption. Many are not even equipped with security professionals on their team and thus lack the technical know-how of implementing security automation into the DevOps cycle.
Concluding the DevOps Discussion
High-octane, fluid collaborative teams, who are highly efficient in delivering ready-to-be-deployed software are what you get by embracing and cultivating DevOps culture at your organization.
No doubt, DevOps is the new normal for SDLCs.
By integrating development and operations teams, and utilizing tools and practices to automate and streamline processes, DevOps has led to faster delivery of software, improved quality, and increased collaboration and communication within teams. However, implementing DevOps requires a cultural shift within organizations, as well as a willingness to invest in tools and training.
Talking of tools, do not forget to explore Hatica, which helps you & engineering managers to unlock greater value, and ensure developer wellness at your organization.
Keep building high-performing happy engineering teams.
Follow the Hatica blog today to read more about agility, unblocking developers, and boosting productivity with engineering analytics.
Here are some frequently asked questions on DevOps:
1. Is DevOps a tool or methodology?
DevOps is a methodology that emphasizes collaboration and communication between development and operations teams, supported by a set of tools and practices that enable security-first, customer-focused continuous delivery and deployment of software.
2. How many stages are there in DevOps?
The stages in a DevOps SDLC may vary depending on the implementation, but in general, it comprises Planning, Development, CI/CD, Deployment, Monitoring, and Maintenance. Security, testing, and compliance are integral parts of all these stages.
3. What are DevOps skills?
DevOps skills include knowledge of programming languages, automation tools, infrastructure management, cloud computing, containerization, and agile methodologies, as well as strong communication and collaboration skills.
4. What are DevOps metrics?
DevOps metrics include lead time, deployment frequency, mean time to recover (MTTR), and change failure rate.