Splunk Observability Cloud Reviews

We utilize Splunk APM for security purposes, monitoring all transactions within the organization to prevent potential attacks. Additionally, we leverage Splunk APM to analyze application logs, gaining insights into application behaviour and facilitating a reduction in Mean Time To Resolution should any issues arise in the production environment.

OpenTelemetry provides more accurate information about an application by combining views from the customer perspective, infrastructure metrics, and application-specific data. This holistic view enables full telemetry observability, allowing us to analyze and strategize effectively for our company or clients.

Once configured correctly, the analysis reporting the Splunk APM provides is better than that of the other APM tools. Once the correct fields are defined, we can create different report dashboards.

Splunk isn't an ideal tool for application performance management due to the extensive setup required. It necessitates various configurations to gather diverse information from applications, networks, or other sources. Creating the right tables and defining the appropriate fields to extract comprehensive data involves a significant amount of setup within the tool. Managing this process can be quite challenging. However, once configured, the collected information is invaluable, although not easily manageable.

Splunk falls short compared to other APM tools such as AppDynamics or Datadog. It does not collect online information in real time and relies heavily on log files. Unlike Datadog, which collects real-time application behaviour data like CPU, memory, load, and response time, Splunk requires additional configuration to obtain similar information. This makes using Splunk for APM purposes significantly more difficult compared to the automatic data collection capabilities of AppDynamics or Datadog.

I have been using Splunk APM for more than a decade.

Splunk APM lacks scalability, requiring the administrator to constantly monitor or create specific alerts to ensure sufficient disk space, CPU, and memory for data collection and transaction processing. This results in a tool that is challenging to manage and costly to maintain.

Splunk support is responsive and provides quick resolutions when tickets are opened. Their service has left a positive impression on me.

Positive

The initial deployment is complex, requiring the definition of the switch, storage, correct host, and working with certification. This necessitates at least one expensive specialist, costing approximately $5,000 per month to hire and work with our team.

Splunk APM is expensive. Even before we begin, we need substantial infrastructure investment to collect comprehensive logs. For example, to gather log data, we must create specific tables in Splunk, starting at 50 gigabytes. In a cloud environment, this storage requirement becomes very costly.

I would rate Splunk APM six out of ten.

Cisco recently acquired Splunk, and its roadmap for the coming year includes incorporating aspects of Splunk into AppDynamics. Cisco's intention behind combining these two tools is to showcase its commitment to open telemetry and comprehensive observability to the market and its customers.

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.

My main use cases for Splunk Observability Cloud include Application Performance Monitoring, Real User Monitoring, and Synthetic Monitoring.

Splunk Observability Cloud has proven to be beneficial for our organization. In evaluating its effectiveness in improving digital resilience within my organization, I have experienced lower costs of unplanned digital downtime.

The solution has helped improve operational performance and company resilience.

Splunk Observability Cloud can be optimized to its full potential. 

I have been using Splunk Observability Cloud since this year.

The stability and reliability of Splunk Observability Cloud has been satisfactory. Customer service and technical support have been evaluated positively.

Splunk Observability Cloud scales effectively with the growing needs of my organization.

Positive

I have always used Splunk products.

My experience with the pricing, setup costs, and licensing has shown a return on investment with Splunk Observability Cloud.

I would recommend organizations to consider implementing Splunk Observability Cloud. 

On a scale of one to 10, I would rate Splunk Observability Cloud overall as nine.

We use Splunk to monitor some devices in the company. We have several cloud groups for monitoring the energy companies in the state. The stack has several devices to monitor if you have a problem. There is a mixture of solutions.

The solution monitors the system in real-time. We can find the resources and investigate security incidents. Splunk and another solution, AppDynamics, monitor several devices.

We integrate Splunk with a data collection solution, and it plugs in the users to collect data at several points in the network and infrastructure. The data is indexed in Splunk, which can be visualized in different dashboards. Monitoring for fraud is critical for the company because you have to resolve many problems in the infrastructure with federal information in the dashboard. 

The company has many systems that the customer pays to access. Splunk APM issued via AppDynamics helps find problems in the feed. It reduces the risk of supervising all the devices. I can supervise the flow and simulate the conditions of the repository across several dashboards to show what's happening at the moment.

The dashboards are used mainly to visualize information about the infrastructure, but it isn't easy to construct or use the dashboards. While we tried to resolve the issue by calling support, it would be easier if they had an AI co-pilot to identify the problem and help you solve it. 

I have been using Splunk APM.

Splunk APM isn't easy to scale because you have to follow the steps and implement best practices, which can be a little awkward.

I rate Splunk support 10 out of 10. We had good documentation, and the support team at Splunk has a lot of experience with code and the tool. 

Positive

I haven't had any problems deploying Splunk. When I installed Splunk for the first time, I thought the product line was complex because I had to build the solution. After working on it for a while, it has become easier to do the solution next time.

Splunk APM is a crucial tool because it controls all the systems and solves a lot of problems.

I rate Splunk APM 8.5 out of 10. It's an excellent solution.

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.

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.

Our primary use case for this solution is as a supplement to Dynatrace, so the log analytics is done in Splunk instead of Dynatrace.

We built a tool for firewall log monitoring and we powered all firewall logs to Splunk. In addition, we built a little dashboard that just specifies sources and the destination addresses and port numbers. It passes all the logs and tell us if there are any blocks or drops on the firewall level. This is a very useful tool for us.

The features I have found most valuable are log searching and log analytics, both of which are quick features.

There's a component in this solution that is particular and takes a lot of manual work and that is the automation. There is a lot of room for improvement with the automation. They should also improve the discovery and detection of all the infrastructure components so that it is more automated and takes less manual work.

I have been using this solution for about five years.

I would rate the stability of this solution an eight, on a scale from one to 10, with one being the worst and 10 being the best.

I would rate the scalability of this solution a nine, on a scale from one to 10, with one being the worst and 10 being the best.

I would rate the technical support of this solution a 10, on a scale from one to 10, with one being the worst and 10 being the best.

Positive

At first, we were deployed on-premises and then about one year ago we migrated to the cloud. So I would say they did most of the work around migration. There are around 1,000 users of this solution in our company.

We have seen the ROI.

I would rate the pricing of this solution a two, on a scale from one to 10, with one being the most expensive and 10 being the best price.

Our model of deployment is the cloud.

I would rate this solution as a whole a 10, on a scale from one to 10, with one being the worst and 10 being the best.

I would advise other people looking into this solution to do their due diligence and make sure they do their pre-work and post-work.

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.

One of the valuable features is that it is very user-friendly. We can directly search for a metric and create alert charts straightaway. There are multiple visualization options to create charts that allow users to create detectors and alerts and integrate them with downstream applications for getting notifications.

Moreover, the volume it handles is very good, including the number of metrics, the volume number of traces, and more.

There are some predefined metrics where we can directly install the SignalFx agent. It gives some informative CPU utilization where some things are inbuilt. But for specific applications, we may need to create customized metrics. Here, developer teams have an additional burden of creating the whole thing if they need to customize anything. The additional feature metric could be a custom metric edition. It would make it simple for any user or engineer to go beyond the default metrics and easily choose to add more metrics. It will help share dashboards, so when we have a single version, thousands of people can use the same single version of the dashboard.

The sharing option and custom metric would be the two additional features I would like to see in the improved version.

I used SignalFx for six to eight months for my previous project, and the version I used was Splunk Observability. I used it last in October 2022; I am not using it right now.

It is a stable product. There used to be some unplanned maintenance or intermittent issues. Most of the time, we used to get alerts or notifications from the SignalFx team. So, out of 100, I would give it a 90. It was stable, but in that 10% of the occurrence, we faced various problems like loading traces, dashboards, and more. In that project, we had a limit of detectors and a limit of a metric time series, and several subscribed metrics. So, we used to get some notifications when it reached 80% or 90% of the usage. Thus, it is completely related to the subscription. But we faced the fact that the number of MTS reached the limit.

In terms of stability, we faced intermittent issues so I won't give it a 100%; it is 90%.

It is scalable. Although the scalability depends on the subscription model, there are some related requests according to cost. For example, if I want to increase the metrics by up to 30%, store more metrics, or create more alerts, I can easily do it without impacting anything. For all those things, it is scalable.

I used to create a support case in the SignalFx portal itself, and I used to call them on their toll-free number and engage them with issues. So I had some experience with their team and I rate them an eight out of ten.

I would rate it an eight because customer support won't provide back-to-back service. If I expect updates every hour, sometimes I may not get updates every hour. For example, if I need someone to explain the issue, there might be delays. If I need to get some root cause of an issue in real-time, that might take time. So considering these factoes, I rate them an eight out of ten.

Positive

I have used some observability tools like Splunk, Instana, and Grafana. I found SignalFx the best one for visualization, and it is user-friendly too. For example, you can directly search for a metric, and we can create alert charts immediately. So there will be multiple visualization options to create graphs. From there, we can directly create detectors, create alerts, and integrate them with other downstream applications for getting notifications.

The initial setup was simple, and we used some package installers. We had a restrictive code for binaries in Artifactory. So we directly used some package installers and pulled it in individual service. Also, it was integrated with Puppet, so installing the SignalFx agent and starting it was simple.

I wanted to manually install, deploy, and download it on a single server, and the whole manual procedure took around 10 to 15 minutes. When I tested a group of services with the help of Puppet, even hundreds of servers were done within an hour or something. 

So I was working on a banking project, and we had a private cloud there; SignalFx agents were installed on servers, and our metrics were derived from there.

My company used an inbuilt application built by in-house developers, which was developed 15 years ago. Those tools were somewhat outdated and could not serve the purpose of the ever-growing volumes and other issues. So they preferred to have some third-party tool to solve their problems, and they found SignalFx useful. As a user, I also thought SignalFx was much better than other visualizations.

I would definitely recommend SignalFx. Compared to other installation tools, creating alerts, understanding charts, and creating dashboards is more straightforward. 

The functions are complex but SingalFx is very user-friendly. There is very defined documentation for everything, whether I have to create an alert or use some aggregation. We will have a direct link that says something like, "Click here to read more" or  "Click here to understand." Such links are there for everything. Moreover, if I want to create an alert, there will be multiple options; it will say, "What is the time of alert?" or "What is the threshold base?" All these details will be there; you will have a link to detailed documentation. It is a very user-friendly tool for any beginner. 

I would rate it as nine out of ten.