12 Popular Observability Tools in 2023
March 17, 2022
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Observability tools help you monitor the performance of your distributed environment and correlate it with your business outcomes.
According to Barr Moses, the co-founder, and CEO of Monte Carlo Data:
Data observability tools, like their DevOps counterparts, uses automated monitoring, alerting, and triaging to identify and evaluate data quality and discoverability issues, leading to healthier pipelines, more productive teams, and happier customers.
Unlike traditional monitoring tools, observability tools provide 24/7, end-to-end visibility into your systems and proactively spot potential issues so that you can mitigate them before they become too serious.
This article presents the most widely used observability tools (DataOps and DevOps), featured on popular review portals such as Gartner and G2.
Here are the twelve most popular observability tools in 2023:
- Monte Carlo Data Observability Platform
- Acceldata Data Observability Cloud
- Appdynamics Business Observability Platform (part of Cisco)
- Amazon CloudWatch
- Datadog Observability Platform
- Elastic Observability
- Instana (an IBM Company)
- Lightstep (from ServiceNow)
- New Relic One
- Splunk Observability Cloud
Monte Carlo Data Observability Platform
Monte Carlo is a data reliability company and claims to have built the first end-to-end data observability platform.
Monte Carlo uses ML algorithms to learn what your data (and consequently, good data) looks like. This helps the platform spot bad data proactively and alert you so that you keep your data clean and credible.
The platform also explores potential data downtime, gauges its impact, and notifies the right folks so that they can fix the issue right away. Here’s how the company defines data downtime:
We’ve met hundreds of data teams that experience broken dashboards, poorly trained ML models, and inaccurate analytics — and we’ve been there ourselves. We call this problem data downtime, and we found it leads to sleepless nights, lost revenue, and wasted time.
Monte Carlo also claims to be the only data observability solution to achieve SOC 2 compliance with their security-first architecture.
What are the main capabilities of Monte Carlo Data Observability Platform?
- Automate root cause discovery to resolve issues faster
- Observe all your data from data lakes, data warehouses, ETL, business intelligence tools, and catalogs in one place automatically and use it to visualize all data dependencies
- Set up the platform without using any code and integrate it seamlessly with your data stack
Monte Carlo Resources
Product tour (Video) | The big book of data observability (Guide) | Documentation
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Acceldata Data Observability Cloud
Acceldata offers a multidimensional observability platform to improve data reliability, optimize data pipeline performance, and reduce inefficiencies.
Acceldata offers three product suites:
- Pulse: For performance monitoring
- Torch: For data reliability
- Flow: For data pipeline observability
The Acceldata product stack integrates seamlessly with the rest of your data stack such as ETL tools and orchestration pipelines.
What are the main capabilities of the Acceldata Data Observability Cloud?
- Predict operational issues before they occur so that the DataOps team can implement fixes
- Use Acceldata Flow to trace the journey of every data asset through your systems
- Automate data reliability across data lakes and data warehouses
Documentation | Acceldata Flow Product Info | PubMatic (Case Study)
Appdynamics Business Observability Platform
The Appdynamics Business Observability Platform is a part of Cisco and was named a “Leader in the 2021 APM Magic Quadrant” by Gartner. The platform lets you connect app performance to customer experience and business outcomes by visualizing every infrastructure component.
Appdynamics integrates well with several languages and frameworks, DevOps tools, cloud environments, mobile IoT, and other such tools in the DataOps tech stack.
What are the main capabilities of Appdynamics Business Observability Platform?
- Unearth root causes of performance issues in real-time to understand what went wrong and how it’s affecting your key business metrics
- Spot app, code, and network security vulnerabilities in real-time
- Use the Smart Code Instrumentation to set up the entire platform in minutes
Datasheet | Case Studies | Analyst Coverage
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Amazon CloudWatch is an observability and monitoring solution for AWS resources. You can collect, access, and correlate telemetry across all AWS resources on a single platform — CloudWatch.
It collects data at every layer of the performance stack, from frontend to infrastructure. You can view metrics graphs for your AWS resources and create alarms to notify you when certain conditions are met (such as an instance CPU utilization exceeding 70%).
Using the data gathered in near real-time, you can identify trends or patterns in your infrastructure’s performance to reduce MTTR (mean time to repair).
What are the main capabilities of Amazon CloudWatch?
- Set alarms and automate actions using either predefined thresholds or machine learning (ML) algorithms to spot anomalies
- Explore, analyze, and visualize your logs to troubleshoot operational issues
- No setup or maintenance needed, and you only pay for the queries you run
Amazon CloudWatch Resources
Amazon CloudWatch | Features | Pricing
Datadog Observability Platform
The Datadog Observability Platform provides complete visibility into the health and performance of your apps, infrastructure, and third-party services. It provides 500+ integrations to bring together end-to-end traces, metrics, and logs so that you can capture and correlate data from any stack in real-time.
Datadog offers a free 14-day trial for its entire platform to help you get started.
What are the main capabilities of Datadog Observability Platform?
- Visualize the status of your microservices in a single pane
- Proactively spot performance issues in real-time with machine learning
- Track incidents with synchronized dashboards
- Analyze and search through logs to troubleshoot issues
- Use Synthetic Monitoring to set up code-free tests and run simulations of any event
Datasheet | Documentation | Resources
Dynatrace’s AI-powered platform uses AIOps to predict and resolve problems before they affect your users or business. Dynatrace offers a single platform that supports hybrid distributed cloud observability, automatic code-level root-cause detection and profiling, DevSecOps automation, and more.
It also supports integrations with 600+ technologies such as cloud services, containers technologies, Kubernetes, and more.
Dynatrace offers a free 15-day trial (no credit card required) to get you started.
What are the main capabilities of Dynatrace?
- Use Dynatrace OneAgent to automate end-to-end data collection, auto-detect all the active processes, and auto-inject the necessary sub-agents to gather the relevant metrics
- Enable distributed tracing and code-level visibility with Dynatrace PurePath
- Get automatic, real-time topology mapping with context using Dynatrace SmartScape
- Scale across hundreds of thousands of hosts, millions of entities, and the largest multi-cloud environments
Quick demos | Documentation | Observability ebook
Elastic Observability is built on the Elastic Stack (also known as the ELK Stack) and enables observability on search to speed up root cause analysis and boost developer productivity.
Elastic Observability integrates with hundreds of technologies and offers apps for APM, logging, and metrics. Moreover, it uses a pay-as-you-go pricing so that you only pay for the hardware resources you used to store, search, and analyze your data.
The 2021 Gartner Magic Quadrant for Application Performance Monitoring named Elastic a Visionary.
The solution offers a free 14-day trial (no credit card required) to help you get started.
What are the main capabilities of Elastic Observability?
- Ingest all telemetry data (metrics, logs, and traces) in an open and scalable platform
- Use traces to identify performance bottlenecks across the entire tech stack
- Leverage searchable snapshots for more log, metrics, and APM data
- Scale both horizontally (by adding more nodes) and vertically (by adding more resources to each node) to support large-scale deployments
Elastic Observability Resources
Documentation | Introduction to Elastic Observability (Webinar) | Elastic Observability 8.1 (Updates)
Instana Enterprise Observability
Instana Enterprise Observability enables end-to-end discovery, mapping, monitoring, and troubleshooting of containerized microservice applications. It ingests all performance metrics, lets you trace all requests, and profiles every process automatically.
Instana offers a free 14-day trial (no credit card required) to the full version of the product.
What are the main capabilities of Instana Enterprise Observability?
- Automate root cause analysis and feedback to ensure optimum performance of your applications
- Proactively discover issues, get answers, and perform a deep analysis with proper context
- Use Instana’s Dynamic Graph (full-stack model), Context Guide (Architectural UX), and Unbounded Analytics (correlated analytics) to understand the correlation between app components and services
Instana Enterprise Observability Resources
Instana’s APM Observability Sandbox (simulation) | Foundations of enterprise observability (ebook) | Documentation
Lightstep Observability was created by the founders and maintainers of OpenTracing and OpenTelemetry. It lets you observe every upstream and downstream dependency, including third-party services, in real-time. You can also use Lightstep Observability to monitor your performance SLAs and SLOs.
Lightstep Observability supports hundreds of languages, frameworks, and platforms and promises to help you spot the root cause of any anomaly in three clicks or less.
What are the main capabilities of Lightstep Observability?
- Understand any change (planned or unplanned) using real-time insights from your tech stack
- Proactively detect changes to your application or infrastructure, and see how it will impact the customers and your business outcomes
- Spend less time troubleshooting with automated root cause detection and analysis
Lightstep Observability Learning Portal | Observability: A complete overview for 2021 (developer guide) | Datasheet
New Relic One
New Relic One lets you aggregate, analyze, and visualize all the telemetry and infrastructure in one place. This helps you detect, triage, and eliminate errors faster. It enables end-to-end observability and integrates with 440+ technologies using pre-built instrumentation, dashboards, and alerts.
Getting started is free. You only pay for the hardware resources you consume at $0.25 per GB.
What are the main capabilities of New Relic One?
- Ingest and search through logs in the right context to correlate events easily
- Automatically spot anomalies or performance issues across all apps, services, and logs and get instant alerts
- Correlate alerts and events from any source automatically to cut down on redundant alerts by up to 90%
- Use NewRelic Lookout to uncover blind spots and unknown relationships
New Relic One Resources
Documentation | Full-stack observability in New Relic One (Datasheet) | 2021 Observability Forecast (Ebook)
Splunk Observability Cloud
The Splunk Observability Cloud integrates the capabilities of NoSample™ Full-Fidelity Ingest, real-time streaming, AI/ML-driven analytics, and OpenTelemetry to improve developer productivity, reduce downtime, and improve the overall release quality and speed.
The products included in the suite are:
- Splunk Infrastructure Monitoring
- Splunk APM
- Splunk RUM
- Splunk On-call
- Splunk Log Observer
The suite of products aims to eliminate blind spots in your tech stack and help you proactively detect problems and resolve them in minutes. The Splunk Observability Cloud can ingest petabytes of data at scale across multiple containers and clouds.
Splunk offers a free 14-day trial to help you get started.
What are the main capabilities of Splunk Observability Cloud?
- Use Splunk Log Observer to go through logs from key DevOps sources in minutes, with no code
- Use Splunk RUM (real user monitoring) to observe web and app performance across every transaction, resource, and third-party dependency
- Identify the root cause of every issue, view everything from a single location, and share details with your team easily
- Automate incident response to reduce mean time to acknowledgment and resolution (MTTA and MTTR)
Overview (Video) | Splunk Observability Suite (Introduction) | Splunk Log Observer (Product Brief)
StackState captures topology time-series data and combines it with telemetry to help you understand why something breaks and how to fix it. So, you can travel back to any point in time and see what your environment looked like before an issue popped up.
You can continuously discover the topology and correlate it with telemetry and traces in real-time. This helps you decrease MTTR, reduce outages, and save the costs involved in detecting and triaging incidents and outages.
StackState offers a free 14-day trial (no credit card required) and even offers a sandbox to try the solution without connecting your AWS or Kubernetes environments.
What are the main capabilities of StackState?
- Automate anomaly detection to flag potential problems and fix them before they affect your business outcomes
- Use a single pane for root cause analysis and impact analysis
- Deploy in minutes without investing engineering resources for configuration and maintenance
StackSlate Sandbox | Features | Datasheet
FAQs on data observability tools
1. What is observability?
Observability is a measure of how well you can infer the internal state of a system using only its outputs. Observability helps you understand the mechanics of distributed applications or microservices in the data ecosystem.
According to Lightstep, observability tells you what’s slow or broken, and what needs to be done to improve performance.
2. What are the three pillars of observability?
Metrics, logs, and traces are the three types of telemetry data that form the pillars of observability:
- Metrics: Understand what went wrong or is causing bottlenecks with the right metrics
- Logs: Learn why something went wrong by going through event logs for your distributed applications
- Traces: Track the path of a request that’s malfunctioning across your distributed infrastructure with traces to understand how something went wrong
3. What are the benefits of observability tools?
Observability tools help you understand how data flows through your distributed environment.
Using observability tools, you can:
- Discover, report, and fix issues (known and unknown) before they affect your customer’s experience
- Set up better ways to debug and fix issues, thereby optimizing the performance of your distributed environment
- Establish a single source of truth for all telemetry (metrics, logs, traces, events)
- Get a real-time picture of the fluctuations in performance and understand your systems better
- Improve incident response time, uptime, and other performance metrics
4. How should I evaluate observability tools?
Each observability tool has its unique features, so it’s important to choose the one that best meets your needs.
Broadly, here are some questions to ask:
- Does the tool help you understand how your microservices behave over time, under various circumstances?
- How does the tool track metrics, logs, and traces? How does it ensure that the data is of high quality?
- Does the tool collect and visualize all relevant data in one place?
- How quickly does the tool alert you to problems? Is it in real-time? And does it offer adequate context?
- Does the tool provide context on incidents — what went wrong, which services were affected, and what was the impact on business or customer experience?
- Does it seamlessly connect to your existing data stack?
- Is it easy to set up, run, and scale?
- Does the tool have reviews or testimonials on popular portals like Gartner, G2, or Capterra?
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- 7 popular open-source data governance tools - to consider in 2023
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