#1 most frequent
United States of America
53.8%1,413 installations of 2,627
What is Elastic Observability?
Elastic Observability, from Elastic, the makers of Elasticsearch, is a solution that aims to bring logs, metrics, and APM based on the former Opbeat (acquired by Elastic in 2017) traces together at scale in a single stack so users can monitor and react to events happening anywhere in an IT environment. It's free and open to start, and adds the Logs, Metrics, APM (formerly Opbeat), and Uptime modules to the Elastic (ELK) Stack.
Categories & Use Cases
Product Demos
Who Buys & Uses Elastic Observability
#2 most frequent
United Kingdom of Great Britain and Northern Ireland
6.7%176 installations of 2,627
#3 most frequent
India
4.6%121 installations of 2,627
My review on Elastic Observability.
Use Cases and Deployment Scope
Elastic observability is mainly used in main problems like Managing many servers of a production deployment. It becomes very difficult to correlate logs and view performance metrics very easily. And Having no ability to detect and resolve these issues by users before they are reported. these are the problems that can be solved by this elastic observability in our company.
Pros
- Open source codebase.
- APM integration.
- Documentation.
Cons
- User Interface.
- Dashboarding.
- Charting issues.
Most Important Features
- Integration
- Deployment
- Customer service.
Return on Investment
- Cost management.
- Good customer increment.
- Time management.
Alternatives Considered
Datadog, Dynatrace and Splunk Enterprise
Other Software Used
Amazon Web Services, SolarWinds Database Mapper, Logstash
Awesome monitoring and search solution
Use Cases and Deployment Scope
Lets us monitor the performance and health of our mission-critical services with the speed of Elasticsearch. I use it for web server log analytics, searching for vulnerabilities and changes to the file logs and system metrics traffic. Elastic Observability has great search functionality and dashboard visualizations and ElastiFlow to monitor the real-time traffic. We save a lot of time. It does the job extremely well.
Pros
- Fast and speedy search engine
- Indexes large amount of data
- Fault tolerance and high availability OOB
Cons
- Difficult to setup/maintain
- Search pattern bar could be more user-friendly
- Premium subscription features are very expensive
Most Important Features
- Logging and Monitoring
- API driven Scalable multi-node architecture
- High availability
Return on Investment
- Migration between versions could require some additional efforts
- Default log format is often difficult to parse
- Understanding the tool for a beginner would be challenging
Good product, excellent service and support.
Use Cases and Deployment Scope
Managing many servers in a production deployment makes it very difficult to correlate logs and view performance metrics. Tracking issues reported by the end-user is nearly impossible (if at all) in a timely manner. These issues cannot be detected and resolved before users report them.
Pros
- Open source code base
- Community support
- Is fast in processing
Cons
- No aspect that interferes negatively.
Most Important Features
- Data analysis
- Anomaly detection
- Open Telemetry compatibility
Return on Investment
- Flexibility to store, search and aggregate any type of data, regardless of data source.
Other Software Used
Microsoft SQL Server, Docker, AWS Lambda
Elastic is a very capable application monitoring solution that can scale easily as your organisation grows
Use Cases and Deployment Scope
We utilise Elastic in our organisation to keep track of all the logs generated by the various internal services that we have running; we utilise it for monitoring in general but a frequent use case involves looking at logs for incident response purposes to figure out what is actually happening and try to understand any potential impact to the application so that we can take steps to avoid any downtime or negative consquences
Pros
- Licensing model is fair compared with other vendors that charge much more
- Ability to scale and ingest a lot of data without having to worry too much about performance issues that may crop up
- Searches return very fast
- GUI searching interface and filters are intuitive and suitable for new users
Cons
- The DSL advanced search syntax query language can be confusing to use as you have to maintain correct JSON formatting at all times
- More integrations with other common alerting/monitoring/ticketing platforms
- GUI hasn't had an update in a while, could benefit from an overhaul with more modern elements
- Default dashboards are suitable but there could be room for improvements e.g. more advanced custom dashboards
Most Important Features
- Ability to relatively cheaply scale your log collection infrastructure as the needs of your organisation grow
- Search results return quicker than in comparable platforms from other vendors
- Reliable operation without crashes or downtime
- Search query language is suitable for most use cases
- GUI interface is not hard to navigate and can be learned quickly by new colleagues without previous experience working with the product
Return on Investment
- Stopped worrying about unexpected licensing costs arising from all the extra logging our applications will generate in the future as our company grows its customer base
- Engineers are happy since product is stable and maintenance is not painful
- Users are happy because search results return quickly
- We stopped having to make concessions in terms of having to filter out certain data which could turn out later on to be valuable and required
Alternatives Considered
Splunk Cloud
Other Software Used
Looker, Google BigQuery, Kibana, Grafana, Prometheus