We use Splunk APM for performance testing. 

Splunk offers end-to-end visibility across our environment.

Splunk APM simplifies application performance monitoring. It also provides insights into data quality, including data security, integration, ingestion, and versioning of trace logs. We can directly inject data for monitoring purposes, trace the data flow, and monitor metric values.

Splunk can ingest data in any format, allowing us to easily monitor logs and identify blockages through timestamps, which saves us time.

The most valuable feature is dashboard creation. This allows us to easily monitor everything by setting the data we want to see. For example, imagine we're working on a project within the application. There might be different environments, such as development, testing, and production environments. In the production environment, we can use dashboards to monitor customer activity, like account creation or other user data. This gives us a clear view of how transactions are performing and user response times. This dashboard creation feature is one of the most beneficial aspects of Splunk that I've used in a long time. While Splunk offers many features, including integration with various DevOps tools, its core strength lies in data monitoring and collection.

Splunk's functionality could be improved by adding database connectors for other platforms like AWS and Azure.

I have been using Splunk APM for one year.

We previously used a legacy application for monitoring and when it was decommissioned we adopted Splunk APM.

Splunk offers a 14-day free trial and after that, we have to pay but the cost is reasonable.

I would rate Splunk APM eight out of ten.

Splunk APM requires minimal maintenance and can be monitored by a team of three.

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.

Detectors are a powerful feature. They create signal flow code in a format similar to Splunk APM language. For example, if we select five conditions, the detector can automatically generate the code for that signal flow. This code can then be directly integrated into our Terraform modules, streamlining the creation of detectors using Terraform. This is particularly helpful because our infrastructure adheres to a well-defined practice, and detectors help automate this process.

APM dashboards are another valuable tool. They provide more comprehensive information than traditional spotlights. One particularly useful feature is the breakdown of a trace ID. This breakdown allows us to see the entire journey of a request, including where it originated, any slowdowns it encountered, and any issues it faced. This level of detail enables us to track down the root cause of performance problems for every request.

We currently lack log analysis capabilities in Splunk APM. Implementing this functionality would be very beneficial. With log analysis, we could eliminate our dependence on Splunk Enterprise and rely solely on APM. The user interface design of APM seems intuitive, which would likely simplify setting up log-level alerts. Currently, all log-level alerting is done through Splunk Enterprise, while infrastructure-level alerting has already transitioned to Splunk APM.

The Splunk APM documentation on the official Splunk website could benefit from additional resources. Specifically, including more examples of adapter creation and management using real-world use cases would be helpful. During our setup process, we found the documentation lacked specific implementation details. While some general information was available on public platforms like Google and YouTube, it wasn't comprehensive. This suggests that others using Splunk APM in the future might face similar challenges due to the limited information available on social media. It's important to remember that many users rely on social media for setup guidance these days.

I have been using Splunk APM for 1.5 years.

While Splunk APM occasionally experiences slowdowns, it recovers on its own. Fortunately, these haven't resulted in major incidents because most maintenance is scheduled for weekends, with ample notice provided in advance. We have never experienced any data loss that occurred during previous slowdowns.

Splunk APM customer support is helpful. They promptly acknowledge requests and provide regular updates. They've been able to fulfill all our information requests so far. However, Splunk APM is a constantly evolving product. This means there are some limitations due to ongoing industry advancements. They are actively working on incorporating customer feedback, such as the CV request. Overall, the customer support is excellent, but the desired features may not all be available yet.

Positive

Previously, we used Grafana, but we faced challenges that led us to switch to Splunk APM. Since then, Splunk has become our primary tool for data analysis. In our experience, Splunk offers several advantages over Grafana. Setting up and using Splunk is significantly easier than Grafana. Splunk provides a user-friendly interface that allows anyone to start working immediately, while Grafana's setup can be more complex. Splunk also boasts superior reliability. Its architecture utilizes a master-slave node structure, with the ability to cluster for redundancy. This ensures that if a node goes down, another available node automatically takes over, minimizing downtime. Ultimately, our decision to switch to Splunk was driven by several factors: user-friendliness, a wider range of features, cost-effectiveness, and its established reputation. Splunk is a globally recognized and widely used tool, which suggests a higher level of trust and support from the industry.

We use Splunk Enterprise and Splunk APM. Splunk APM offers a comprehensive view of various application elements. We primarily migrated to APM to gain application-level metrics. This includes latency issues, which are delays in processing user requests. Splunk APM generates a unique trace ID for each user request. This allows us to track the request from the user to our servers and identify any delays or errors that occur along the way. 
Additionally, Splunk APM utilizes detectors to create alerts based on specific metrics. We've implemented alerts for CPU and memory usage, common issues in our Kubernetes infrastructure. We can also track container restarts within the cluster and pinpoint the causes. Another crucial area for us is subscription latency. Splunk APM allows us to monitor this metric and identify any performance bottlenecks. This capability was absent in Splunk Enterprise, necessitating the switch to APM. Furthermore, Splunk APM enables us to track application status codes, such as 404 errors.

Splunk APM facilitates the creation of informative dashboards using collected metrics. Additionally, the Metrics Explorer tool allows us to investigate specific metrics of interest and generate alerts or customized spotlights. 
Spotlights are tailored visualizations that track metrics for critical application areas. They can trigger alerts based on unexpected changes, such as a sudden increase in error codes over a set timeframe. This provides a more proactive approach to identifying potential issues compared to traditional detector-based alerts.

Splunk APM empowers us to effectively monitor various metrics during load testing. This includes analyzing memory usage across ten to eleven metrics, tracking container restarts during flow testing, and verifying the functionality of auto scaling mechanisms. The comprehensive visualization capabilities of Splunk APM surpass those of Splunk Enterprise, making it ideal for analyzing large sets of metrics and graphs.

We're currently exploring the integration of an OpenTelemetry agent with Splunk APM. This will enable us to collect and transmit a wider range of data, including application metrics, latency metrics, and basic infrastructure metrics such as CPU, memory, etc.

During the initial Splunk deployment, I found that most information available on social media platforms catered to enterprise deployments. Fortunately, many of our new hires had prior Splunk experience, which eased the initial learning curve. Splunk's widespread adoption across industries also meant there was a general familiarity with the tool among the team. Additionally, the comprehensive documentation proved helpful. Overall, the initial rollout went smoothly, though there were some challenges that we were able to resolve.

The Splunk deployment was done on multiple environments. We started with development and then deployed to a staging environment, which sits between development and production. As expected, the development deployment took the longest. The total time for the entire deployment, including my cloud setup, was 2 to 3 weeks. It's important to note that this timeframe isn't solely dependent on Splunk implementation. Other factors can influence the timeline, such as network requests, firewall changes, and coordination with IT teams for license purchases. While the development deployment took longer, promoting Splunk to the staging and production environments was significantly faster. It only took 1 week for each environment.

Our cloud deployment didn't require a consultant, but we used one for our on-premise enterprise deployment, which was a bit more complex.

I would rate Splunk APM 9 out of 10.

The maintenance required is minimal because the cluster deployment helps ensure there is always 1 node working.

I have the logs of my applications, and they're usually a bit volatile. The log switch doesn't stay there on the application for a long time, so Splunk can require that. It can take 15 days for the logs to be available to do some kind of research. I'm using Splunk to ingest application logs, create dashboards, and set up alerts. 

The biggest benefit of Splunk is that we can retain logs and correlate the data. Telemetry data has a huge impact because it's much easier to see everything. 

Splunk has significantly reduced our mean resolution time. The workflow at my company involves application microservices applications running on the cloud. These logs are highly volatile, so they're only retained for three to five minutes, and we had to reproduce an issue to trace why it failed. That meant we had to do everything again to capture the log at the moment.  Now, we have the data to analyze one or two hours.

Splunk's dashboards are great. The solution provides end-to-end visibility across my environment. Visualizing large amounts of data is easier because we can correlate the data from any target source. 

The licensing model is expensive. We need to monitor the amount of data ingested because the cost is based on the data collected. 

I have used Splunk APM for three years now.

We have instances for production and development. I've never seen the production instance go down. Our development instance has gone down, but that's expected. 

I used tools like Elasticsearch, which is similar to Splunk. I've also used other observability tools like Grafana and Dynatrace, but they have different features.

I rate Splunk APM 10 out of 10.

We mostly work with developers. They run some pipelines, and they use Splunk as a platform to identify the errors, instead of themselves debugging the logs and understanding what the issue is. This is one side of the business. On the other side of the business, we use the Splunk database for frozen buckets where we archive the data.

We can easily integrate it with other tools for monitoring our entire IT data infrastructure. I also handle AppDynamics. We have integrated Splunk and AppDynamics. With one click, we can understand what the actual issue is. It brings down the time to resolve. We have had some good experiences.

It improves our operational efficiency every day. In my previous company, we had integrated it with ServiceNow. For defined alerting conditions, it could directly open up a ticket for the right team. We did not have to look into a thousand cases to understand a problem.

In terms of integrations, most of the plugins are already available. If a plugin is not available, even then it is pretty easy to integrate. There are multiple ways to integrate. You can use the REST API and just forward the data. It can be easily integrated.

It makes it easy to have end-to-end visibility in the cloud environment. There are multiple types of devices in an environment. You might have AWS, Microsoft Azure, or something else. It operates beautifully. It is easy to integrate. This is the best part.

I am in the banking industry. It helps to keep track of how well our application is performing when somebody tries to do a transaction. There are multiple pieces to it, and we keep track of everything. We have our own business dashboard that the top-tier leaders can look into. All the visibility is there because of it.

I find the monitoring console very helpful. With one click, I can see how we are performing, and at the same time, I can see what data is flowing.

The clustering part of indexes can be more refined.

They can cut down a bit at the monetary level for the long-time customers. We recently had a scenario where we were in discussions to see if there was any flexibility from Splunk's side.

I have been using this solution for the past two years. I have also used it in my previous company.

It is pretty scalable. I would rate it a nine out of ten for scalability.

I have worked with Kibana and Logstash, but they are not comparable to this solution.

It is expensive.

Overall, I would rate it an eight out of ten.

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 data collection from our VMs, containers, databases, and backend components is valuable.

Splunk Infrastructure Monitoring's data analytics can be improved by including suggestions for various types of continuous monitoring.

I have been using Splunk Infrastructure Monitoring for three years.

The network uptime and monitoring are great.

The scalability of Splunk Infrastructure Monitoring is excellent.

The technical support is good.

Positive

We previously used Datadog but it doesn't offer network monitoring features like CPU utilization or overall server performance, which Splunk Infrastructure Monitoring does, so we switched.

Splunk Infrastructure Monitoring offers more functionality and visibility, making it a better choice for handling cloud architecture compared to Datadog.

The initial setup was straightforward. One person was required for the deployment.

I would rate Splunk Infrastructure Monitoring 9 out of 10.

Splunk Infrastructure Monitoring offers automated, continuous monitoring and diagnostics, delivering real-time reports for all your data with enhanced functionality compared to other solutions.

We have 200 users of Splunk Infrastructure Monitoring.

Splunk Infrastructure Monitoring is the best solution for monitoring networks, parameters, CPU, memory usage, and network traffic cases. 

I use it for monitoring and troubleshooting the performance of cloud-native applications.

Providing comprehensive visibility throughout the environment, it monitors my system, enhances career performance, and offers insights into the user experience.

Troubleshooting and visualizing a cloud-native environment is made easy with Splunk APM. It provides complete visibility into software tools, swiftly monitoring business performance and applications.

It possesses the capability to conduct distributed tracing within our environment. This includes monitoring the speed of tracked access, extending from end users to the Internet, system, and network services, and supporting my software application. Consequently, it offers an end-to-end overview of potential bottlenecks.

Splunk APM has significantly enhanced our organizational efficiency. Initially, my responsibilities included tracking website application performance, managing applications, and handling license releases. Now, it provides real-time user monitoring, transforming the way I handle these tasks.

It significantly impacts our organization's telemetry data, improving operational performance and user experience. The platform provides insights into application performance and effective log management. Ensuring accurate tracking of all performance-related logs contributes to building up the application performance percentage with comprehensive data.

It contributed to a daily reduction of six hours in our mean time to resolve.

The most valuable features are troubleshooting and optimizing application performance. 

Another value lies in the resilience and quick recovery capabilities offered by the SIEM. It enables thorough monitoring across our landscape, providing insights into the number of running software applications. The tool furnishes comprehensive information across microservices, significantly enhancing our proficiency.

Enhancing system availability and optimizing service performance are crucial. It is essential for the monitoring tool to deliver quick response times when generating analytical reports, instead of prolonged delays.

I have been using it for two years.

It provides good stability capabilities.

It has the capacity to scale. There are approximately two hundred users and one administrator that use it.

I would rate its customer service and support eight out of ten.

Positive

The initial setup was straightforward.

The deployment process took six hours. During this time, a clear understanding was established regarding which technical applications—whether cloud-based, native, or others—needed monitoring and improved performance. These categories were identified in-house, with two individuals overseeing the process.

It allowed our IT staff to focus on other projects by freeing up their time. In total, it saved around four hours.

We evaluated Grafana.

It can serve as an analytical application for enhancing performance, ensuring all dependencies are effectively addressed. Overall, I would rate it eight out of ten.

I use Splunk primarily from a gateway operations perspective. I work on application support. As part of that support, we regularly monitor the application dashboards built in Splunk using the logs. I covered this earlier this month.

The real problem we were facing was that we were unable to get all of our logs into a single place. We have an on-premise application with multiple servers across different data centers, and we needed to be able to view all of the logs together in order to troubleshoot any problems. That's why we started using Splunk to forward all of our logs to a single location.

Moreover, Splunk APM gives us end-to-end visibility across our entire on-premise environment. 

Another biggest benefit I've seen is the ability to quickly identify problems using Splunk alerting. We set up alerts against our application metrics, and this has helped us to resolve major issues much sooner. We can now identify problems as soon as they occur, which gives us time to take corrective action before they impact our users.

Splunk has reduced the amount of time our operations team spends investigating problems. This has freed up our engineers to focus on other tasks, such as improving our application performance and adding new features.

I like the fact that Splunk APM makes it easy to connect to the application database and run queries against the data. I also like the fact that Splunk APM allows me to use log forwarders to forward logs to a central location, where I can then build dashboards to view the data. The dashboards are probably my favorite feature of Splunk APM.

I've been using the Splunk query language, and it can be a bit time-consuming to set up the queries I need. I've had to look at a lot of community forums to find the filters I need, and it can be difficult to get the details I need.

I have experience building dashboards and other things with Splunk APM.

I've been using Splunk APM for over a year now. As part of my job in application support, I regularly create and maintain dashboards for our applications using Splunk APM. I also use dashboards to create alerts based on certain metrics.

Moreover, I'm currently working on a project to create a new dashboard for our customer support application.

The stability of the solution is good because I have never had outages I have seen so far. In terms of usage, it's good in terms of availability.

I haven't had to contact the support yet. We have a separate team that maintains and builds our relationship with Splunk, so they would be the ones to contact if we had any issues.

The solution doesn't require any maintenance. 

We used New Relic and AppDynamics before Splunk. AppDynamics was our APM tool, and I'm still using New Relic for monitoring Splunk. New Relic is great for log monitoring, and it's our main tool for internal application monitoring.

With Splunk APM as an enterprise solution, various factors come into play. Right now, considerations include pricing and how they envision the solution to work for them. Some might want the solution to be cloud-based. It largely depends on the volumes they anticipate. Organizations must decide how much they're willing to invest, especially when comparing it to other investments they've made. With the current economic recession and organizations looking to cut costs, it's crucial to evaluate the volumes and aspects of Splunk that are most relevant to them.

Overall, I would rate the solution an eight out of ten. 

We use Splunk Infrastructure Monitoring because it is a durable solution for our environment.

Splunk Infrastructure Monitoring is easy to use.

The dashboards are good.

Splunk Infrastructure Monitoring has helped improve our operational performance and efficiency. 

Splunk Infrastructure Monitoring has helped reduce our MTTD by 90 percent.

Our MTTR is good thanks to Splunk Infrastructure Monitoring.

The most valuable feature is log reporting.

The price has room for improvement.

I have been using Splunk Infrastructure Monitoring for five years.

I would rate the stability of Splunk Infrastructure Monitoring ten out of ten.

Splunk Infrastructure Monitoring is scalable.

I have used the technical support a few times and they were good.

Positive

I would rate the price of Splunk Infrastructure Monitoring as an eight out of ten, with ten being the most expensive.

I rate Splunk Infrastructure Monitoring ten out of ten.

Splunk Infrastructure Monitoring is a good service that provides visibility into our environment.

I recommend Splunk Infrastructure Monitoring to organizations for the logs that will help identify errors in their devices and assist them in resolving the issues.

One person is required to maintain Splunk Infrastructure Monitoring.

In my company, we use Red Canary MDR to perform MITRE ATT&CK, after which I import the lot or whatever commands were run by Red Canary MDR to my Splunk system for further analysis. I use a type of real-time monitoring by Splunk.

The most valuable feature of the solution is the way it formats the raw data and helps make the understanding process much easier for the users. When you see the unformatted lots, it looks gibberish, especially for first-time users who may not understand a lot of things, but using Splunk Real User Monitoring (RUM) can make their job easier.

I had tried onboarding Splunk Real User Monitoring (RUM) on the cloud, but unfortunately, I couldn't onboard it on the cloud. It is an issue from my end that Splunk can try to improve.

I have used Splunk Real User Monitoring (RUM) for over half a year. I use the solution with an enterprise license for a trial period of six months. I am a customer of Splunk.

It is a stable solution.

Everyone in the SOC team, consisting of 50 to 100 people in my new company, uses Splunk Real User Monitoring (RUM).

The initial setup of Splunk Real User Monitoring (RUM) was easy.

The solution is deployed on-premises.

My company decided to go with Splunk Real User Monitoring (RUM) over other solutions since it has the ability to format raw data making the job of the organization easier.

I recommend the tool to those planning to use it since even though similar tools are available in the market, Splunk Real User Monitoring (RUM) is easier to use, especially for businesses.

I rate the overall solution a nine out of ten.