More and more software development companies are adopting DevOps to deliver software quickly by taking advantage of resilient infrastructure and product ownership. DevOps practices continue to break down organizational silos and integrate the development and operations teams.
As more companies rush into DevOps, they often regard this methodology as the “universal solution” to all their limitations. This leads to poor implementation and undesirable results. Increasingly, we find DevOps implementations plagued by problems linked to legacy infrastructure and low uptime. Gartner estimates that in 2023, 90% of the DevOps implementations will fail to meet expectations due to reasons like this.
A recent example of a DevOps failure is that of Knight Capital which collapsed within 45 minutes of a failed deployment. High downtime and non-availability of the DevOps infrastructure are among the major reasons for these failures.
Here is a detailed look at the various DevOps challenges – and how to address them effectively. Keep reading on.
Uptime and Availability Challenges in DevOps
Server uptime and service availability are among the crucial metrics for measuring the reliability of any DevOps implementation. The presence of legacy systems and applications can create roadblocks to a successful DevOps implementation.
Here is a look at the major challenges that impact uptime and availability in the DevOps system:
- Obsolete practices
Organizations are adopting DevOps to transform their software development lifecycle (or SDLC) processes. However, they continue to pursue legacy or obsolete processes and practices in specific places. For instance, companies fail to break down organizational silos – or use dedicated teams for product development, operations, and testing.
Besides the use of outdated technologies, “siloed” teams usually have minimum communication and collaboration during DevOps projects. Despite all the automation, successful DevOps implementation requires seamless communication among the involved teams. How does this factor impact uptime? Team collaboration improves the quality of bug tracking and resolution, thus delivering high-quality products.
- Poor incident management
Many DevOps teams are in the mode of responding to an incident after it has occurred. This means that most reasons for failures are not understood or forgotten. Historically, DevOps teams have faced challenges in process monitoring.
With its numerous moving parts, the DevOps workflow uses different metrics to test their effectiveness. For example, metrics like deployment frequency are used for monitoring a CI/CD pipeline, while the defect escape rate metric is used in continuous testing.
DevOps environments lack clear visibility over their processes, thus resulting in production delays. Besides, manual processes can cause human errors, thus causing downtime or non-availability.
- Cloud security risks
DevOps projects rely on flawless cloud infrastructure and deployments. This can expose applications to external security threats, which can reduce their uptime and availability. Besides, DevOps teams use a host of containers and other tools to accelerate their application delivery. In this environment, a small bug or misconfiguration can potentially crash the entire cloud application.
As portable platforms, containers have simplified the process of application deployment. However, IT security teams cannot determine the level of container security, nor address questions about security-related risks. Besides this, a lack of communication between the development and security teams can result in delayed releases and frustration.
- Legacy applications
Development companies are moving from legacy applications to microservices to maintain their competitive edge. By replacing legacy applications with microservices architecture, they can increase the pace of development and innovation. However, this transition also comes with its share of challenges. Among the major challenges, increased complexity can lead to an increase in application downtime and unavailability.
How does Reliability Engineering address these DevOps challenges? Let’s discuss that next.
How Reliability Engineering can address DevOps challenges
What is reliability engineering? Also referred to as Site Reliability Engineering (SRE), this discipline is designed specifically to improve the availability and scalability of any DevOps application. Originating as a concept from Google, SRE uses software technologies and tools to manage IT infrastructure, resolve problems, and automate tasks.
Reliability engineering can improve application performance and system efficiency by:
- Ensuring that all transactions are complete without any errors.
- Automating the process of detecting and resolving issues on time.
- Improving team collaboration and eliminating organizational silos.
- Reducing failure rates and system downtime.
Here are some ways that reliability engineering can resolve DevOps challenges:
- Improved incidence management
SRE teams can proactively prevent failure incidents with their incident management process. They can identify and classify incidents based on their urgency and prioritize them according to importance. After conducting a complete “postmortem” of the incident, SRE practices can identify the areas of improvement. This information helps build a secure and resilient DevOps system.
- Reduction in organizational silos
The SRE discipline shares ownership among the development and operations teams. A recent survey found that 55% of developers spend only up to 25% of their time on development-related tasks. Reliability engineering removes this imbalance.
With this approach, SRE teams can focus on monitoring performance and detecting issues. Development teams can focus on product features and bug fixing, while the operations team can focus on managing the underlying infrastructure.
- Continuous monitoring
To identify performance issues and maintain availability, SRE teams must continuously monitor the DevOps systems. Real-time monitoring validates if applications are performing as expected.
Using the following service level commitments, organizations can monitor their system performance:
- Service Level Agreements (SLAs) are the agreements with internal and external customers.
- Service Level Objectives (SLOs) are the defined goals necessary to achieve the SLAs.
- Service Level Indicators (SLIs) can measure the actual performance indicators against the SLOs.
- Reduced human errors.
Among its main objectives, SRE aims to eliminate or reduce manual and repetitive tasks. SRE teams spend 50% of their time reducing manual effort. Effectively, SRE focuses on implementing automation technologies for the entire DevOps team. Besides reducing human error, this practice ensures that all teams are using the same technology tools. This reduces any chances of failures occurring due to incompatible systems.
In the age of DevOps, reliability engineering can complement DevOps practices and improve its uptime and availability. On its part, SRE improves functions like application monitoring, incidence management, and team collaboration. This is why SRE is now essential in any DevOps environment.
At Forgeahead, we offer our customers high-quality DevOps consulting services that enable them to build resilient and high-performing systems. We can provide you with a free estimate for your next DevOps project. Talk to our software consultants.