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What is Observability ?

Gursimran Singh | 09 Mar 2023

What is Observability ?

Introduction to Observability

Observability is the ability to measure a system's internal states by looking at its outputs. If the current state of a system can be determined solely from information from outputs, such as sensor data, then the system is said to be observable.

What is Observability?

Observability is a way to get insights into the whole infrastructure. It is essential for the operations team. It means assembling all fragments from logs and monitoring tools and organizing them in such a way that gives actionable knowledge of the whole environment, thus creating insight. It is a combination of multiple items to create a deep understanding of the actual health, real issues, and what should be done to improve the environment and troubleshoot at a root level.

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It means the service can explain any questions about what is happening on the inside of the system just by observing the outside of the system without entering a new code to answer further questions. Software is enhancing exponentially extra complexity. It is a term from the control method. It is a test of how well the inner states of a system can be assumed by knowledge of its external outputs. The Observability and controllability of a system are numerical duals. It might mean various points to various characters. For unusual, it's about logs, metrics, and traces. To others, it's the first wine of monitoring in a fresh container.

  • Creating and operating an extra-visible system
  • A system that can explain itself without the need to deploy new code
  • Understanding connections between parts of your background or System
  • No complex system is always healthy.
  • Categorized systems are pathologically unpredictable.

What is Monitoring?

Monitoring is the routine inspection and reporting of activities taking area in a project or program. It is a method of routinely collecting information on all phases of the project. Monitoring tools examine the infrastructure log metrics to perform actions and insights. The monitor is to check on how project activities are improving. Features of monitoring tools are:
  • To recognize the problems and send an alert message to the dashboard
  • To log real-time and historical data
  • Monitor the figure of users on a network
Troubleshooting/ Debugging and root cause analysis
  • Goal address threats to customer satisfaction
  • Debug novel problems in production
  • There needs to be data to explore
  • A quantitative examination can help you obtain the business case to address an issue.
  • Retrospectives instill confidence that issues won't happen again
A Platform for Monitoring, Logging, Tracing and Visualization of Big Data Cluster and Kubernetes with ML and Deep learning. Click to explore about, Observability for Kubernetes

Importance of Observability

There must be feedback to run the Continuous integration (CI) and continuous delivery (CD) processes. It doesn't make any sense to push out changes without acknowledging if they continually make things better or worse. The "Monitor" Part of the DevOps circuit gives the all-important feedback that drives future repetitions.

Site Reliability Engineering Approach

Site reliability engineering (SRE) is Google's way of service management, where software engineers work production systems using a software engineering approach. It's explicit that Google is different, and they usually need to catch Software bugs and errors in various and non-conventional ways.
  • Site Reliability engineering reliable operating system and infrastructure scale.
  • Define metrics that matter most to the business, typical values for those metrics, and plan a reaction if the value isn't met.
  • Service level indicator, service level objectives, service level agreement
  • RED: The acronym stands for Rate, Errors, and Duration. These are request-scoped, not resource-scoped, as the USE method is. Duration is explicitly taken to mean distributions, not averages.
  • The increase means time to failure (MTTF), and the decrease means time to repair (MTTR)

Service level objective (SLO)

There is usually difficulty in using Service Level Agreement (SLA) and Service level objective (SLO). The SLA is a complete understanding of what service is to be given, how it is maintained, times, locations, costs, performance, and responsibilities of the people involved. SLOs are specific measured properties of the SLA, such as availability, throughput, repetition, response time, or quality. Certain SLOs usually are meant to define the demanded service between the provider and the client and vary depending on the service's needs, resources, and budget.
  • NO SLO < Good SLO < Perfect SLO
  • Pick an objective and iterate
  • Capture a set of events and use a window and target percentage of 99.9% of an event good in the last 30 days.
  • A good SLO is barely user happy.
  • Determine an error budget that allowance of failure in the tradeoff is not allowing for progress and innovation.

    What are the Observability Pillars?

pillar-of-observabilityWhat is Logging?

Logs: A record of an event that took place at a given time

  • Support by most libraries
  • Disciplined to put meaning logs into your code
  • Aggregate logs to avoid overshooting them
  • Java logging classes and a logging properties configuration file writing to STDOUT.
  • Flaunted used to scrape, process, and ship logs
  • Stored in a persistent data store, such as an electric search, a distributed analytics engine
  • Queried directly or interacted with using kibana, a customizable visualization dashboard
  • Choose a tool to capture and analyze logs.
  • Plain logs report force is a free-form text. This is also the usual standard format of logs.
  • Structured logs have been much converted and advocated for in recent days. Typically, these logs are issued in JSON format.
  • Think logs in the Protobuf form, MySQL binlogs applied for replication and point-in-time improvement, system journal logs, the pflog format accepted by the BSD firewall pf that often serves as a frontend to tcpdump. What are Metrics?

Numeric aggregation of data describing the behavior of a component or service measured over time 

  • Accessible to store and model
  • Beneficial to understand standard system performance
  • Supported by most libraries
  • JAVA matrices classes that push data to a metrics endpoint

What is Tracing?

Tracing is used to capture a request flow of a causally related event.
  • Each has requested a global ID- metadata inserted at each step in the flow as the ID is passed along.
  • Distributed tracing System like Jaeger or Zipkin is used to visualize and +inspect traces.
  • Open Telemetry:- A language- Neutral approach to tracing
  • Forks in performance flow like OS thread
  • A fan-out over channels or process boundaries

Service Mesh

A service mesh is a process of managing how various elements of an application share data with each other.
  • The configurable infrastructure layer for the Microservice application is used to control east-west service traffic.
  • Monitor and control the progress of transactions through your cluster.
  • Sidecar pattern or node agents/ daemon set pattern.
  • Logs and metrics are gathered for free reduced tracing.
Integration with open-source observability tools like Garfana, Prometheus, jaeger, and Kaili- prepopulated with the dashboard
A non-functional type of testing that measures the performance of an application or software under a certain workload. Click to explore about, Performance Testing Tools

Importance of Observability

Following are the reasons why it matters
  • Enables transparency across applications deployed in the environment.
  • Observability helps document the production environment and get the information needed to improve it.
  • It helps to understand what’s going on behind the scenes.
  • It allows for catching unknown issues quickly and helps understand how to handle them.
  • Detecting issues without it in place is hard.
  • Allows feedback loops essential in DevOps movement.
  • Enabling it inside the environment is very important.
  • It helps developers and DevOps guys find insights and bottlenecks in applications and trace information.
  • Its importance increases in real production environments to prevent downtime. Proper alerting should be in place.

How does Observability work?

To attain the ultimate state of observability, consider the following -

Logging Process

Logging is a mechanism to collect logs from various input sources. Usually, logs are in raw format. To gain real insights, parse these logs, and apply query type to gain insights quicker. Usually, logs are sent to an output tool that organizes the logs. Logging defines what to log, how it should be logged, and how logs shipped to an external system for aggregating. Debug mode is disabled for better logging as logging everything based on a debug level will become really expensive to manage, creating extra false positives, not-so-important alarms, and more difficulty in getting important data. Debug should be the default only while troubleshooting, not in real production environments.

Monitoring Process

Monitoring is an activity performed by DevOps guys. It’s simply observing the state of an infrastructure/environment over a period of time. Monitor for three reasons - Detecting Problems – Usually by alerts or looking at issues on dashboards. Finding Resolution for Problem – Finding root causes of issues and troubleshooting. Continuous Improvement – Reporting and documenting.

Tracing Working

Trace the calls between various applications. Priorities are defined as different service failures, and the one with the highest priority is caught and alerted immediately. Tracing shows what either happened in the past or what is happening at present. Tracing is a very important piece of it proactively. It also suggests what code we can add to the service to provide better insights into the application. There should be transparent visibility end to end for all transactions happening in the environment.

How Alerting Works?

Alerting helps define how to notify the Ops guys when an event occurs. False positives it is very important to remove them. There should be -
  • Alert only to important events.
  • Self-healing infrastructure.
  • Enable analytics when something has been done manually many times.
  • Enable Automation to fix the problems.
Monitoring of applications is the biggest aspect, As the speed and the accuracy expected is very high to address the issue on time. Click to explore about, Application Performance Management in DevOps

Benefits of Observability

  • Observability helps to understand what’s going on in production, makes it work better for end users, and eliminates the need for debugging in a Production environment.
  • Monitors the performance of applications.
  • Helps in identifying the root causes of issues and helps in troubleshooting.
  • There are many intuitive dashboards high to observe what is happening in Real-Time.
  • Allows Self-healing infrastructure.
  • It helps in enriching the data and provides information faster. Encouraging developers to use tracing helps them to see how what they’re doing on an everyday basis maintains it and improves the overall application and its infrastructure.

Best practices of Observability

It is essential to discipline in DevOps. To Adopt it, Along with logs ingestion, Dev should add code to the applications to be able to provide more additional and insightful data to enable alerts. Devops run automated end-to-end tests on a daily basis, before and after deploying applications, to understand if deployment broke anything or not. It should be the responsibility of both the Dev and Ops guys. The developer provides appropriate logging data, which makes sense and is useful for getting insights, and proper error codes for requests. It reduces outage time while Ops teams troubleshoot. Both Dev and Ops guys add value to Observability to achieve full success.
Following Best Practices followed while allowing Observability for applications running in the environment -
  • Do not Monitor everything.
  • Monitor only things that are essential to fix when they fail.
  • Do not put Alerts on everything.
  • Put alerting only for critical events.
  • Do not store all logs and all data.
  • Store only logs that give insights about critical events.
  • Don't use default graphs.
  • Create a custom graph according to customer needs.
  • Create alerts based on Prometheus or Grafana metrics of running applications in an environment.
Java vs Kotlin
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List of Top Observability Tools

Various Monitoring Tools

Deployment tools

  • Containers and Orchestration tools such as Docker and Kubernetes.
  • Log Aggregator
  • AWS Cloudwatch

Alerting Tools


Observability enables infrastructure. At first, applying this is a little change of mindset and adding new tools in place, but once proper Logging, Monitoring, and Alerting are in place, it will be beneficial on a daily basis and in the long term. Plan to deliver applications in modern ways, spend more time debugging and adding operational visibility tools to optimize the speed of troubleshooting and ultimately automate them.