Monitoring vs Observability: Building Observability in Cloud-Native Microservices


By RevDeBug

To effectively run the CI/CD process, you need feedback. It would be best if you had observability over components and the ability to monitor performance.

DevOps relies on gathering in production insights and feeding that data back into development — allowing developers to harness actual outputs to improve future iterations.

Although “monitoring” is the traditional operating tool category within the DevOps toolchain, microservice architectures create issues that standard APMs (application performance monitoring) struggle to surmount. There is a movement to build complete ‘observability’ platforms that can deliver the kind of context-rich data that DevOps demands.

Fundamentally, observability and monitoring are not the same things. The demands of microservices and cloud-native environments (although designed to enable the incremental innovation of DevOps) are putting the modern DevOps toolchain to the test.

New answers are needed. Here, we are going to discuss the advances in monitoring tools that have delivered true observability within cloud-native architecture and how you can upgrade your DevOps toolchain for cloud-native and microservice deployments to grab a competitive advantage in 2019.

Observability vs. monitoring

One way to differentiate between control and observability is to define monitoring as the task of collecting data and observability as something achieved once that data is made available.

More useful monitoring vs. observability distinction is between how applications are performing and what is going on. Monitoring sticks to tracking how applications are performing — telling you about bottlenecks, access speeds, downtime, and connectivity. Observability drills down into the why and what of application operations — delivering specifics on the reasons for errors that monitoring can only tell you about the existence of them.

Why observability and monitoring are both critical

It would help if you had high-level tools that can tell you about the health and functionality of your system as a whole. It would be best if you also could zoom in and understand what has gone wrong in the event of an error.

The reality is that an error will inevitably arise; nothing can be perfect. In this context, both observability and monitoring capabilities are required. True observability platforms are your ultimate insurance policy — a critical investment to confidence in the face of reality.

Neither observability or monitoring is new. For example, logging has been the traditional method used since the dawn of programming. Similarly, for decades, Modern APMs have been a staple of Operations teams. Although both are considered DevOps tools, all based on outdated logging techniques unfit for the modern era, as neither provide true observability in cloud-native or remote environments. Neither lives up to the needs of the modern DevOps toolchain.

Defining cloud-native and microservices

Cloud-native is a buzzword. It is also a useful term describing several real technologies that enable modern applications to best take advantage of the dynamic scaling opportunities delivered by the cloud and CI/CD strategies of DevOps.

Cloud-native references microservices and serverless architecture. These two architectures are very similar. The big difference is in hosting — both split applications into specific functions using virtualization technology — enabling flexibility and on-demand use. With serverless, however, those functions are hosted by a third party — for example, AWS or Azure. It magnifies the on-demand capabilities.

Microservice and serverless disaggregation can be achieved using VMs. However, this is increasingly done using containers. Containers (enabled by platforms like Docker and Kubernetes) bringing VM abstraction down to the application layer, allowing the best and most modern languages to be used within subsections of a single application.

Consternation makes it easy to add features and replace components in isolation without jeopardizing the data or application’s operations on the whole. Sections can be written only to be switched on under specific requirements.

Cloud-native can be used to describe any one of these three technologies. Most often, it represents microservice or serverless environments enabled by containers.

The problem of observability in microservices and cloud-native

Microservices (and serverless) have quickly created new best practices for application development. However, they have smuggled in a dilemma. Using traditional tools, it is impossible to keep track of what is going on within these distributed environments. This challenge is primarily created by the multiple dependencies this kind of architecture introduces. The isolation of containers (often used to develop microservices) adds to the problem. So, too, does the accelerate speeds of DevOps and CI/CD release cycles.

Microservices create too many sources of information to track

When you break apart your application, you create dozens, if not hundreds, of micro-applications. Each of these micro-applications needs to be monitored.

Incumbent APM tools can provide you with information on the health of your system as a whole. Using traditional tools, looking into the next layer of what is going on, is done by logs.

Fundamentally, gaining true observability using standard logs in a microservice architecture is impossible. Applications executing billions of instructions per second, along with multiple dependencies, create far too much information to capture. Even if you could catch it, you are still stuck with a disjointed and decontextualized mess that your engineers must trawl through to try and understand the issue, let alone reproduce it and hope it works.

Using traditional tools, monitoring is possible; true observability is not

Using traditional tools, dev and ops teams are alerted of a failure by an APM. However, they are then stuck guessing at what went wrong. Days, weeks, or even months are spent trying to reproduce an issue.

Often real root-causes are never found, and tech-debt is expanded, creating ad hoc fixes that don’t address the real issue. This stops the DevOps CI/CD approach to the rapid development that containers are designed to enable. User experiences are damaged, innovation stifled, and ultimately revenue affected.

True observability platforms built on in-production, software flight recorder technology

True observability in microservices is here, delivered by a new breed of Software Flight recording platforms that offer almost zero performance impact during runtime, providing a 100% reproducer of every production error in real-time.

Test software flight recorders — record and replay

Software flight recorders have become an observability staple in test and development, allowing devs to jump back and forth through code and receive a contextualized information feed about what exactly happened during an error. Armed with flight recorder, root-cause analysis is simplified, delivering the best means to solve problems fast.

The limitation of software flight recorders has always been an impact on runtime performance. Standard expectations are for a 10x, 100x, or more slow down in application execution. Sometimes, this slow down can be accommodated in a test, but it still causes problems. Moreover, it rules out the deployment of these tools in production environments.

In-production observability

A new emerging breed of software flight recorders has fully resolved this issue. Rather than instrumenting the application slowly at runtime, the instrumentation is done at compile-time, working with the compiler optimizations, so that runtime instrumentation requirement is almost zero. The result is a less than 10% performance impact. Optimizing for specific environments can reduce this impact further down to less than 5%.

The ability to bring software flight recorder technology into production creates many possibilities. By itself, this delivers far greater observability, even for microservice environments. The contextualized detail of what is going on within applications can be passively captured and rapidly access when needed — across the entire distributed architecture.

There is no longer a need to reproduce errors that affect your customers — the exact steps, within the specific ingredients that cause the failures, are known immediately the error occurs.

True observability

True observability is delivered by augmenting the use of in-production software flight recorder technology with monitoring and automation tools — creating an ultimate APM solution that is capable of providing root-cause analysis, even in cloud-native environments.

Monitor dashboards providing heat maps of global production deployments and errors, including a 100% reproducer of the mistake in real-time, can be accessed through integrated DevOps and Executive monitoring tools. Automated rollbacks providing a “Self Healing DevOps pipeline” can be executed to “last known good versions” within milliseconds of an error. What is offered is production monitoring, and industry fastest root-cause analysis rolled into one.

True observability tools complete the DevOps toolchain

True observability is central to the CI/CD pipeline. The more information DevOps has about how code operates within production environments, the more effectively DevOps can leverage agile strategies to innovate.

DevOps is built on the feedback and incremental change. Microservices enable change. With true observability platforms, not only is the total amount of accessible, actionable information increased, the challenge of capturing that information within a microservice environment is removed. Detailed and granular information is obtained without damaging performance, and rapid root-cause analysis is guaranteed.

This gap within the DevOps toolchain has been closed, and the production environment (even using containers, serverless architecture, remote client devices, and air-gapped environments) can provide the feedback DevOps needs to succeed.

Monitoring and observability are not the same — both are needed, and now both are delivered. Risks are reduced, innovation improved, and observability maximized. A fix fast or die approach to DevOps is enabled, and cloud-native capabilities are taken to their true potential and deliver the on-demand enterprise revolution.


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