Splunk Observability Cloud Reviews

We use Splunk in APM to monitor our applications. So, we integrated it into our systems to enhance our monitoring and observing capabilities, especially for our microservices. 

So, we have used Splunk APM for this.

APM integrates well with Splunk’s other observability solutions. These logs with application performance monitoring can significantly impact our business in several positive ways, like troubleshooting and root cause analysis. 

Using these logs with APM, we can collaborate performance metrics with log data. It allows us to pinpoint the exact cause of issues, such as identifying specific errors in the logs. Because of this, we have access to faster resolution and detailed logs alongside performance metrics, enabling quicker diagnosis and resolution of problems. It also helps us minimize downtime and improve system reliability. 

Additionally, it improves our performance optimization with detailed insights and analyzing historical log data along with APM metrics. This allows us to understand long-term trends and make informed decisions about performance improvements and better user experience, like error reduction and proactive monitoring.

Splunk has reduced our mean time to resolution by 30%. 

If there is any issue in Splunk; we’ll identify the issue first and look for the error messages, like alerting with the Splunk user interface or in the logs that might indicate what the issue is and then determine which part of Splunk is affected. 

Then, we’ll refer to the Splunk official documentation and check the system's health. We’ll review the logs. By following these steps, I can resolve the issues with Splunk, ensuring that our monitoring and analytics capabilities remain effective.

I use the solution in my company primarily for distributed tracing and metrics troubleshooting. I use the tool to troubleshoot incidents and find the root cause of errors when something goes wrong. I also personally use it to have a developer's understanding of what is going on in my application. Sometimes, there is a case where you might put your application in a library or a new library, and that library also makes calls somewhere. Splunk APM's monitoring can show you that there is a call you are making now that you never used to make in the prior version of the library. In these cases, which you may not know just by looking at the external view of the application code, the tracing part traces everything, including the lowest types of supports.

The main benefit of the tool I have noticed in the solution is reduced time for the resolution of incidents. The meantime to resolve can help pinpoint the root causes of the issues because you see the connections on the graph in Tag Spotlight. It is easier to pinpoint who is responsible for the incident, especially when you have a larger organization. You have teams that ride services where they need to talk to different services from different teams rather than having to hand off instant resolutions from one team to another. You can often find it much more quickly from the first instance of the problem occurring with the product in place. The tool specifically helps your sites move up more frequently, and then when it does go down, the solution finds the root cause and gets it back up as fast as possible.

We use Splunk APM to understand and know the inner workings of our cloud-based and on-premises applications. We use the solution mainly for troubleshooting purposes and to understand where the bottlenecks and limits are. It's not used for monitoring purposes or sending an alert when the number of calls goes above or below some threshold.

The solution is used more for understanding and knowing where your bottlenecks are. So, it's used more for observability rather than for pure monitoring.

The solution's service map feature allows us to have a holistic overview and to see quickly where the issues are. It also allows us to look at every session without considering the sampling policy and see if a transaction contains any errors. It's also been used when we instrument real use amounts from the front end and then follow the sessions back into the back-end systems.

We use Splunk APM to monitor the performance of our applications.

Splunk APM offers end-to-end visibility across our entire environment. We need to control how many types of metrics are ingested by Splunk APM from all incoming requests. While we allow some metrics to be collected, Splunk APM provides the ability to track each request from its starting point to its endpoint at every stage.

Splunk APM trace analyzer allows us to analyze a request by providing its trace ID. This trace ID gives us a detailed breakdown of how the request entered the system, how many services it interacted with along the way, and its overall path within the system. We can also identify any errors that occurred during the request's processing and track any slowness or latency issues. This information is very helpful for troubleshooting performance problems in our application.

Splunk APM telemetry data has been incredibly valuable. While we faced challenges with Splunk Enterprise, such as the lack of a trace analyzer, Splunk APM's user interface is modern and highly flexible. The wide range of data it provides has significantly improved our incident response times, allowing us to quickly create alerts and adhere to the infrastructure as code principle. Splunk APM also proves beneficial during load testing, contributing to a positive impact on our overall infrastructure performance analysis.

Splunk APM helps us reduce our mean time to resolution. With its fast and accurate alerting system, we can quickly identify the exact location of issues. This pinpoint accuracy streamlines the investigation process, leading to faster root-cause analysis.

Splunk APM has helped us save significant time. We're now spending less time resolving production incidents and analyzing performance data. This focus on Splunk APM allows us to dedicate more time to other areas.

We use the solution to monitor and calculate the number of systems, applications, and DR sites we have. Then, if there is any problem, we can detect the information on which server belongs to which application. This really helps us.

We have seen 28% to 29% optimization and performance with Splunk Infrastructure Monitoring. You will know the moment you see any anomaly in the system, the server, or the infrastructure. The solution has given us more visibility not only from the infrastructure or server point of view but also from the network perspective.

We use Splunk Infrastructure Monitoring to monitor our hybrid infrastructure.

We implemented Splunk Infrastructure Monitoring to help us monitor our infrastructure as we scale.

Splunk Infrastructure Monitoring is easy to use. It helps us quickly analyze how our infrastructure is performing across various services.

It helps with proper log management, allowing us to monitor our systems and analyze log data regularly. It also provides security operations capabilities for monitoring system health and ensuring uptime. We noticed these benefits immediately.

Our operational efficiency has been increased. It has improved our system health by monitoring the performance of data on servers, virtual machines, and containers, along with overall background processes.

Splunk Infrastructure Monitoring provides end-to-end visibility into our cloud-native environment. This is crucial because any data corruption can impact all the information we've deployed. It also aids in log management, offering parameters that extend its functionality as a comprehensive monitoring tool for CPU, memory usage, and network traffic.

It has helped reduce our mean time to detect by four hours.Our mean time to resolution has been reduced by two hours. By providing access to all our network parameters, it simplifies log ingestion through streamlined calculations.

Splunk Infrastructure Monitoring provides us with faster and more comprehensive insights into our infrastructure, allowing us to focus on critical business initiatives.

We saw the time to value immediately after deploying Splunk Infrastructure Monitoring.

The main purpose of using Splunk APM is to optimize our application. We use Splunk APM primarily to understand how the application works, how it uses resources, and its response time in connection with different infra services. It is mainly used for application optimization and reviewing third-party application dependency response times.

Splunk APM helps us to identify long-running queries and long-running functions or methods, as well as third-party dependencies that are not responding on time. We are easily able to see the error or trace it. A developer can easily find out the issue without having to dig into the application.

We normally do not use the Tag Spotlight functionality, but our developers use this functionality when we are trying to dig into the logs. It helps to search the data that we want to see. It helps to troubleshoot the actual problem and visualize the data. We can see how the error is coming and how many reports are coming.

Splunk APM has helped us to optimize the application performance, find out when third-party services go down, and monitor our application within our SLA. It allows us to minimize our downtime. We can send timely notifications to our users. It mainly helps us to optimize application performance, and secondly, we are able to generate alerts based on the data that we receive from Splunk.

Splunk APM helps us to find errors immediately and resolve them. We are able to find some of the errors within five minutes. It minimizes the time to identify errors. There are about 30% to 40% time savings.

Our primary use case for SignalFx was visualization, charting, and alerting. We also used it to fix our µAPM.

For one project I was working on, at least 15,000 people were using SignalFx. They used to monitor their application health in the SignalFx dashboard and get alerts from SignalFx. The users had different job profiles, such as engineers and architects.