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Overcoming the Complexity of Microservices Monitoring and Alerting

Brad Griffith October 08, 2019

DevOps Monitoring & Alerting
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Microservices and containerized applications are dominating software development and IT operations everywhere. CI/CD and cloud-native software development has led to a need for containerization to maintain reliable services without slowing velocity. Microservices, particularly in containers, drive more scalable workloads and, in most circumstances, simplifies app development and maintenance.

While breaking applications into microservices can offer a lot of overall complexity, the individual pieces become easier to manage and build from. For instance, if a single module fails, microservices allow you to minimize the blast radius of an incident, leaving the rest of the system intact. Additionally, microservices create a system where small fixes can be deployed quickly and can be built out based on the ever-changing needs of the business.

But, for all the benefits provided by microservices, there are a number of challenges, particularly around observability. Service abstraction can cause a lack of visibility into application and overall system health, leading to more unnoticed incidents and the potential for greater end-user impact. For instance, microservices offer greater fault tolerance for individual applications and servers. But, because of the interconnected nature of microservices, there’s more potential for failure and errors within the network.

So, we decided to put this post together as a guide to overcoming the complexity of microservices with a specific plan for monitoring and alerting.

The challenges with observability and microservices monitoring

Developers and IT professionals who’ve taken a mindset of DevOps and adopted the Agile methodology will have an easier time monitoring and alerting with microservices. Automation and collaboration across all facets of the software development lifecycle (SDLC) are imperative to effectively monitor and alert on a microservices architecture. Config management, CI/CD servers, APM, network monitoring, dashboards, alert automation and incident management tools should be commonplace for most teams running microservices.

Microservices need to constantly interface and communicate with each other, which can lead to network and application performance issues such as latency and slow responses. And, although microservices can allow developers to write code in the programming language of their choice, microservices still need to be able to play nice with each other. So, effective management of the network between numerous microservices becomes the priority when looking at reliability in a microservices, container-based system.

If you can do a decent job of monitoring disparate microservices and creating visibility into service health across teams, you can likely tackle the major pain points associated with microservices. Microservices monitoring isn’t simply about installing Splunk, SignalFX, Prometheus or Sysdig to identify problems and visualize service health – it’s about having a plan once you do notice something wrong. So, now we’ll dive into the alerting process and how you can establish an incident response plan that works for microservices architecture.

Monitoring & Incident Response

Why the alerting process matters

When working with microservices, observability and comprehensive IT monitoring are required to eliminate blind spots, establish “healthy” benchmarks for metrics and logs, and create incident action plans. Without context, you can’t create rules around alert automation and surface the right information to on-call responders when they need it. Then, you can track incident management KPIs to show how effective you are at detecting, responding to, and remediating incidents in production.

Purpose-built alerting and collaborative incident management solutions can ensure on-call responders know exactly when something’s wrong and how they can fix it. You can create alert rules based on microservices and teams to ensure the right person gets alerts when they need them. And, alongside on-call calendars, everyone knows who’s on-call and responsible for specific areas of the architecture at any given time.

With alerting and on-call schedules built into one tool where you can manage IT tickets and collaborate in real-time, you’re establishing a culture dedicated to uptime and transparency. Disparate teams managing disparate microservices can work across silos and find resolutions to problems at any point in the software delivery or incident management lifecycle. With that in mind, let’s dive into 5 areas where you can easily improve microservices monitoring and alerting.

5 areas to improve when monitoring and alerting with microservices

  • Monitor containers AND their contents

Containers running on Kubernetes or Docker continue to gain traction and make it easier to build microservices. But, because of their nature as small, isolated processes with little to no dependencies, many DevOps and IT teams think they can simply monitor the container as a whole. However, without also monitoring the contents inside of a container, you’re missing out on valuable monitoring context.

Observable microservices depend on distributed tracing across all applications and infrastructure, leading to the ability to see what’s actually going on inside of a container. It’s important to understand failures, errors and incidents at the greater container level but you’re ignoring the specifics of your containerized application if you don’t monitor the contents of your containers.

  • Alert on services, not containers

Similarly to the point above, don’t only establish alert rules around container metrics and their overall uptime. Again, it’s important to alert on this information but you also need to know when processes are failing inside of a container. While containerized microservices can help limit the failure across the rest of the application, you still want to mitigate container failure as much as possible. And, by monitoring and alerting on key metrics and logs within a container, you can detect problems and notify on-call responders more quickly – often leading to an incident resolution before it can affect end-users or other dependencies.

  • Holistic, automated monitoring across multi-location, elastic services

Hybrid cloud architecture, distributed operations, CDNs and load balancers can make it harder to understand and gain visibility into the complete system. But, their benefits toward performance, reliability and development speed typically outweigh the lack of observability. Kubernetes or Mesos are continuously spinning up new containers and cloud infrastructure on AWS or GCP will spin up new servers at will – potentially causing a lack of visibility into new services.

Hybrid cloud environments and containers, built across multiple cloud services and on-prem servers need to configured and monitored differently. So, you need to leverage automation and build a monitoring system that can span between all of these containers and datacenters to continuously monitor and establish a metrics baseline that indicates a healthy overall service.

  • API and endpoint monitoring

Microservices depend on APIs and endpoints to communicate with each other. So, naturally, you need consistent, detailed monitoring across all of your APIs and endpoints. Not only to monitor performance, latency and error rates, but so you can create benchmarks for overall service health based on the cumulation of all interconnected APIs and endpoints between microservices. Because of the importance of network performance when maintaining a microservices architecture, APIs and endpoints are crucial to the success of the operation.

  • Organize monitoring and alerting based on microservice and team structure

When taking on microservices, you need monitoring and alerting processes to align with team structure. So, look at how you’ll break down the application into microservices, who’s responsible for those microservices and assign accountability and on-call responsibilities to the corresponding teams. A centralized incident management tool can digest multiple sources of monitoring metrics and help DevOps and IT teams correlate alerts and route them to the right team. You can set up on-call teams and alert rules based specifically on how you’ve built out your microservices architecture.

Building and maintaining observable microservices architecture

Last year, DZone published an article showing that 63% of enterprises are adopting microservices architectures. Containers and microservices are helping DevOps and IT teams deploy new features faster than ever before and generally improving the reliability of the services they maintain. But, observability and cohesive monitoring and alerting in microservices will be a constant battle. A DevOps culture focused on automation, collaboration and continuous improvement across all engineering and IT disciplines can help facilitate more reliable microservices.

Greater exposure to production and cross-functional visibility between developers and IT professionals also leads to more visibility in technical systems. Microservices monitoring and alerting are bolstered by looking at the right things, continuously updating benchmarks and finding new ways to track service health across disparate containers and services.

See how VictorOps – a collaborative, real-time incident management and alerting tool – can help you build and maintain more robust microservices. Sign up for a 14-day free trial or request a personalized demo to make the most out of your monitoring and make on-call suck less.

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