We performed a comparison between Elastic Observability and Google Cloud's operations suite (formerly Stackdriver) based on real PeerSpot user reviews in five categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: Elastic Observability is a more comprehensive option with machine learning and custom development, but has a steeper learning curve. Google Cloud's operations suite is praised for its user-friendliness, scalability, and stability, but has mixed opinions on pricing. Elastic Observability is a more economical option for application performance monitoring.
"It's easy to deploy, and it's very flexible."
"The solution is open-source and helps with back-end logging. It is also easy to handle."
"The architecture and system's stability are simple."
"We can view and connect different sources to the dashboard using it."
"Good design and easy to use once implemented."
"The price is very less expensive compared to the other solutions."
"Machine learning is the most valuable feature of this solution."
"I have built a mini business intelligence system based on Elastic Observability."
"The features that I have found most valuable are its graphs - if I need any statistics, in Kubernetes or Kong level or VPN level, I can quickly get the reports."
"The most valuable feature is the multi-cloud integration, where there is support for both GCP and AWS."
"Provides visibility into the performance uptime."
"Our company has a corporate account for Google Cloud and so our systems and clusters integrate really well."
"The cloud login enables us to get our logs from the different platforms that we currently use."
"We find the solution to be stable."
"Offers a valuable logging transport feature"
"I like the monitoring feature."
More Google Cloud's operations suite (formerly Stackdriver) Pros →
"Elastic Observability needs to have better standardization, logging, and schema."
"The solution would be better if it was capable of more automation, especially in a monitoring capacity or for the response to abnormalities."
"Elastic Observability is an excellent product for monitoring and visibility, but it lacks predictive analytics. Most solutions are aligned with the AIOps requirements, but this piece is missing in Elastic and should be included."
"There is room for improvement regarding its APM capabilities."
"There's a steep learning curve if you've never used this solution before."
"The tool's scalability involves a more complex implementation process. It requires careful calculations to determine the number of nodes needed, the specifications of each node, and the configuration of hot, warm, and cold zones for data storage. Additionally, managing log retention policies adds further complexity. The solution's pricing also needs to be cheaper."
"The solution needs to use more AI. Once the product onboards AI, users would more effectively be able to track endpoints for specific messages."
"The auto-discovery isn't nearly as good. That's a big portion of it. When you drop the agent onto the JVM and you're trying to figure things out, having to go through and manually do all that is cumbersome."
"The product provides minimal metrics that are insufficient."
"It could be even more automated."
"This solution could be improved if it offered the ability to analyze charts, such as a solution like Kibana."
"Lacking sufficient operations documentation."
"It is difficult to estimate in advance how much something is going to cost."
"If I want to track any round-trip or breakdowns of my response times, I'm not able to get it. My request goes through various levels of the Google Cloud Platform (GCP) and comes back to my client machine. Suppose that my request has taken 10 seconds overall, so if I want to break it down, to see where the delay is happening within my architecture, I am not able to find that out using Stackdriver."
"It could be more stable."
"While we are satisfied with the overall performance, in certain cases we must add additional metrics and additional tools like Grafana and Dynatrace."
More Google Cloud's operations suite (formerly Stackdriver) Cons →
More Google Cloud's operations suite (formerly Stackdriver) Pricing and Cost Advice →
Elastic Observability is ranked 7th in Application Performance Monitoring (APM) and Observability with 22 reviews while Google Cloud's operations suite (formerly Stackdriver) is ranked 27th in Application Performance Monitoring (APM) and Observability with 10 reviews. Elastic Observability is rated 7.8, while Google Cloud's operations suite (formerly Stackdriver) is rated 8.0. The top reviewer of Elastic Observability writes "The user interface framework lets us do custom development when needed. ". On the other hand, the top reviewer of Google Cloud's operations suite (formerly Stackdriver) writes "Good logging and tracing but does need more profiling capabilities". Elastic Observability is most compared with Dynatrace, New Relic, AppDynamics and Azure Monitor, whereas Google Cloud's operations suite (formerly Stackdriver) is most compared with AWS X-Ray, Datadog, Azure Monitor, Amazon CloudWatch and Dynatrace. See our Elastic Observability vs. Google Cloud's operations suite (formerly Stackdriver) report.
See our list of best Application Performance Monitoring (APM) and Observability vendors, best Log Management vendors, and best Cloud Monitoring Software vendors.
We monitor all Application Performance Monitoring (APM) and Observability reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.