In a little over a year, we’ve covered the future of APM (Application Performance Monitoring) and the expansion of APM into observability. This is followed by a race between software vendors to define observability. Recently, we looked at the evolution of an overview shared by industry-leading software vendors.
To bring clarity to the subject of observation, this article will answer the following questions:
- What is observability?
- What is the difference between observability and monitoring?
- What are the best observability software and tools available?
- How is OpenTelemetry standardizing observability?
- What about security overview?
Leading software vendors have completed the range from traditional monitoring to full overview. However, there is still a knowledge gap for customers interested in the observation. As a result, some are feeling a bit cloudy about the observability for the cloud – no pun intended.
Let’s first go back and look at what observability is and then how it fits in with traditional monitoring practices.
What is observability?
So, what exactly does observability mean? Let’s start with the official definition. as defined by Wikipedia, “Observability is a measure of how well the internal states of a system can be predicted from the knowledge of its external outputs.”
Observability is a superset of surveillance.
Without monitoring you cannot have observation.
We are already familiar with traditional surveillance. So, observability is simply a superset of surveillance. All elements of monitoring are also elements of observability. See above diagram. The term observability has been defined and applied to cloud computing to obtain actionable insights using full-fidelity data.
Why is observability important?
Well-performing applications are critical to the growth of many online businesses and organizations that require observation supported by traditional monitoring methods.
Monitoring is necessary to have observability into the inner workings of your system. Adds additional insight by using observability matrix, tracingAnd Logging.
Observability Metrics, Tracing and Logging (Telemetry)
by Peter Borgen,
Let’s see the importance of matrix, tracingAnd Logging as described in the book Distributed Systems Observability By Cindy Sreedharan:
- matrix It is a numerical representation of the data measured over an interval of time. Metrics can use the power of mathematical modeling and prediction to gain knowledge of the behavior of systems at present and in the future over time intervals. Since numbers are optimized for storage, processing, compression, and retrieval, metrics enable data to be retained for longer periods of time and easier to query. This factor makes the metric perfectly suited for building dashboards that reflect historical trends. Metrics also allow the data resolution to be gradually reduced. After a certain period of time, the data can be aggregated into daily or weekly frequencies.
- tracing – It represents a series of causality-related distributed events that encode the end-to-end request flow through a distributed system. Traces are representing logs; The data structure of the trace looks almost like an event log. A single trace can provide visibility into both the path traversed by the request and the structure of the request. The path of the request allows software engineers and SREs to understand the various services involved in the path of the request, and the structure of the request helps to understand the junctions and implications of asynchronous in the execution of the request.
- Logging – Logs are immutable, time-stamped records of discrete events that have occurred over time. Essentially a timestamp and a payload for each event context.
Observability provides valuable information about your applications, but without context the information is often too little or useless. So when determining the health of applications, the observable platform should help put things into context.
Therefore, observable platforms are needed to digest the raw data, then extract and present the important information in context. This is why observation is an active process that goes beyond simple warnings. It tells you why something went wrong and provides enough context so that you can fix it.
What is the difference between observation and monitoring?
Monitoring vs Observability Simultaneously by paperdata,
Observation and monitoring may sound like the same thing, or at least be very similar. When deployed, the two work in tandem. However, they are not the same.
Observability goes beyond simply monitoring application availability, performance or capacity status to help you resolve issues quickly. As I mentioned, it dives deeper by collecting and analyzing full-fidelity data in real time to provide an interactive and detailed context of what’s happening, why, and how to solve it.
What are the Best Observability Software and Tools Available?
Observability provides alerting, metrics overview, query tracing, and log analysis. , Grafana Labs
20 Observability Software Vendors and Tools I Recommend (In Alphabetical Order)
Observability software vendors pushing for more third-party integration, open-source support and allowing for open standards are best positioned to emerge as leaders in this market in 2021 and beyond.
Here’s my seller-neutral list of current leaders in overview.
Last Updated: August 16, 2021
- AppDynamics – Full-stack observability to drive business decisions.
- eternity – Digital Experience Management, and more.
- broadcom – AIOps and Observability.
- datadog – Modern monitoring and security for the cloud edge.
- dynatrace – Automatic and intelligent observation.
- elastic – Integrated visibility across your ecosystem.
- epsagon – Modern overview for modern applications.
- Grafana , Observability platform, integrating metrics, traces and logs.
- of honeycomb – Overview for modern engineering and DevOps teams.
- court – APM Observability Sandbox. (acquired by IBM)
- lightstep – Full-context overview.
- logic monitor – One platform, automatically correlate data.
- management engine – 90+ observable products and tools.
- Microsoft – Overview for applications, infrastructure and networks.
- new relic – Observability Made Simple.
- open telemetry – An observability framework for cloud-native software.
- Oracle – Cloud Observability and Management Platform.
- prometheus – Flexible monitoring system and time series database.
- orion – Overview using Appoptics, Pingdom, Loggly, and more.
- splunk – Full-stack, analytics-powered and enterprise-grade observability cloud.
The list continues. Suggestions and Editing for consideration always welcome.
- Alibaba Cloud – End-to-end monitoring platform.
- Amazon Cloudwatch – Overview for AWS resources and applications.
- cribbly – Providing control and flexibility for observability data.
- google cloud – Collect metrics, logs and traces across Google Cloud and across your applications.
How is OpenTelemetry standardizing observability?
As noted above, the adoption of observability is increasing due to the increasing availability of software vendors and other solutions. However, this trend requires telemetry data (metrics, tracing and logs) to be as vendor-agnostic as possible.
Traditionally, telemetry data has been provisioned by open-source projects or commercial software vendors. Along with the lack of standardization, the net result is a lack of data portability that places the onus of maintaining the equipment on the user.
open telemetry The project addresses these problems by providing a single, vendor-agnostic solution. OpenTelemetry is a collection of tools, APIs and SDKs that provide you with:
- A single vendor-agnostic instrumentation library per language, with support for both automatic and manual instrumentation.
- A single collector binary can be deployed in a variety of ways, including as an agent or a gateway.
- An end-to-end implementation for generating, emitting, collecting, processing and exporting telemetry data.
- Full control of your data with the ability to send data to multiple destinations in parallel through configuration.
- Open-standard semantic conventions to ensure vendor-agnostic data collection
- Ability to support multiple reference propagation formats in parallel to help migrate as standards evolve.
- The way forward no matter where you are on your observation journey. Adoption of OpenTelemetry is easy, with support for a variety of open-source and commercial protocols, formats and context propagation mechanisms, and OpenTracing and OpenSense projects providing shims.
The project is seeing increased industry support and adoption from cloud providers, vendors and end user.
What about security overview?
The state of online business is changing, and there is no doubt that observation is essential. However, there is now a huge opportunity and challenge created by delayed conversions regarding security overview (application security).
Software vendors and organizations should prioritize application security as quickly as they prioritize and establish observability. A more integrated, standardized and collaborative approach to observation would yield many security dividends.
Cyber security, as we discussed last time, will continue to dominate the news headlines in the coming months. As such, security will emerge as an important component of observation, with the addition of context to the collected telemetry data.
Being able to proactively detect runtime application vulnerabilities, then seamlessly mitigate or connect to third party solutions for mitigation is a conversation we should be having right now.
Some of the providers above are already doing the same with specific offerings for application security.
For the past two years, there has been a shift towards remote working and at the same time, there has been a significant increase in online traffic. As a result, implementing observability has become mission-critical for companies.
In many cases, organizations are using a combination of traditional monitoring and observable software solutions to generate, emit, collect, process, and export telemetry data.
This change has given rise to a variety of vendor solutions, programming languages, APIs, etc. This requires that observable leaders now focus on third-party integration, open source, open standards, and a more integrated approach overall. In addition, there is a need to reduce the complexity involved in combining multiple observable software vendors and open-source software solutions.
As always, I’m not here to support one vendor over another, so when it comes to observability, observability context, security observability, etc., feel free to add your feedback, suggestions, and questions below.
For more specific case-by-case vendor recommendations, contact me.