Elastic Observability Reviews

“It really has convenient boards

Pros

The dashboards are super handy and provide all the necessary information at once.

Cons

The query language is proprietary and can be difficult to master.

“Excellent tool for managing incidents

Pros

It's really easy to use and when you pair it with ElasticSearch, it becomes even more powerful.

Cons

I can't think of any major cons but it does take some time to get familiar with the tool at first.

“A game-changer for IT processes

Pros

The product is always improving, adding new tools to ensure that various technologies are well-monitored and integrated. The open community allows users to share solutions for different use cases and the combination of open-source code, community support, frequent updates and new features makes this product stand out. The best part is the open source availability of Elastic Search's integration with the stack.

Cons

Constant updates require regular configuration changes and maintenance but the quality of the documentation helps make this manageable.

“It works seamlessly with Elasticsearch and Kibana, simplifying data ingestion and transformation

Pros

Logstash does an excellent job of ingesting and transforming data, and then storing it in Elasticsearch. It can process nearly any data as long as you're willing to put in the setup time. We use it for collecting logs from various sources, transforming them and storing them in Elasticsearch. Kibana then helps with dashboards and analysis. It's perfect for this use case.

Cons

Setting it up can be tricky especially since it's mostly command-line based with configuration files. The recent Log4j issues also made us rethink how we approach log shipping, transformation and ingestion. If similar vulnerabilities crop up in the future, it could impact the system in ways that aren't immediately obvious due to how logs are processed.

“Super fast search for billions of log files in a second

Pros

I have been using Elasticsearch for over three years now with Graylog and Elastiflow, and it's super fast. I can search through 20 million messages in just a few seconds. It's incredibly powerful especially for real-time data processing. The flexibility it provides in visualizing the data is awesome and I highly recommend it for enterprise log systems.

Cons

It's working well overall but it can be a bit complicated for someone who is new to it.

“A fast-paced company with innovative products

Pros

Elasticsearch has evolved from being just a tool you integrate into other systems to a fully customizable, standalone solution. Now it's a one stop solution so you don't even need third-party plugins or extensions.

Cons

The licensing models can be confusing, and there's a strong push toward their hosted SaaS offering but that itself is also not very clear.

“One of the top open-source search engine, delivering quick and efficient search

Pros

Adding it to most projects boosts the performance of full text or JSON document searches. It's commonly used for searching through log files (especially with the ELK or EFK stack). While setting up Elasticsearch used to be more complicated, it's much easier now thanks to containerized setups like Helm charts. We use it for general search and as a key part of our logging stack.

Cons

There are a lot of configuration options, which means there's some ramp-up time needed. Plus, the change from Apache 2.0 to SSPL licensing and the split between projects due to Amazon's involvement doesn't help the community or customers.

“Easy to set up

Pros

I loved how easy it was to set up and get going in our environment with minimal effort, research or trial and error.

Cons

The Elasticsearch clustering process was my least favorite part of the setup. There were a lot of small configuration details to address.

“The industry standard in search technology

Pros

The overall performance is excellent. It handles large amounts of data easily and provides near-instant response times. Plus its built-in features for failover and high availability are great out-of-the-box. Being open-source is a huge advantage too. The ELK stack is one of the best tools for analyzing logs.

Cons

It can be tough to set up and maintain even for technical users, so you might need to rely on support services and better analytics. Migration between versions might also require extra effort due to breaking changes.

“Great tool for data storage

Pros

It's a super useful tool for storing and searching data. The initial setup for logging might seem complex, but once you get the hang of it, it's really easy to use.

Cons

To fully utilize the service, there's definitely a bit of a steep learning curve which is a problem.

“The top choice in the market

Pros

It's user-friendly especially considering it comes with the full ELK stack, which not only stores data but also collects logs (via Logstash) and visualizes them (via Kibana).

Cons

I haven't come across anything I dislike so far.

“The ultimate tool for managing your logs

Pros

it boasts a huge community, is open source, has a powerful REST API, is well-documented and also can be installed easily with just a few commands. You don't need to have in- depth database knowledge and it integrates smoothly with third-party software.

Cons

Some of the premium features (like those in X-Pack) require a subscription, which can be quite expensive. Plus if you want a subscription, you need to have at least three licensed nodes.

“A fantastic solution for data search

Pros

It's perfect for managing application and server logs at scale. When combined with Kibana as part of the ELK stack, it's incredibly powerful and extremely useful.

Cons

It can be difficult to understand at first especially during setup but once configured properly, it works really well.

“Loved its flexibility

Pros

Elasticsearch comes with several built-in advantages, including scalability through sharding, powerful aggregation features, schema flexibility and excellent full-text search options.

Cons

It's query DSL is less flexible and less common compared to other solutions, and everything is indexed by default, which can lead to some overhead.

“My go-to search engine!

Pros

We primarily use Elasticsearch alongside Kibana and Logstash to create a full stack for log evaluation and analysis and it works like a charm. It's a powerful and complete search engine.

Cons

It is powerful but the cons include its heavy resource requirements and the complexity involved in learning it. It takes time to get up to speed before you can tackle more complex tasks.

“Using the ELK stack for effective monitoring and logging

Pros

This is hands-down the best software stack for data analysis and searching. We stream data into it, index it and can search and analyze it in real time. It performs really well and the fact that it comes as a managed service on cloud providers means minimal maintenance overhead.

Cons

Nothing else really stands out as a con, except that JSON is the mandatory data format, unlike Apache Solr, which is a competitor.