Splunk Observability Cloud

My experience with Splunk Observability Cloud  involves monitoring infrastructure, application performance monitoring, and real-time alerting. Although I am no longer working with Splunk Observability Cloud  due to a recent position change that occurred approximately two months ago, I previously monitored servers, containers, Kubernetes , application performance, and Docker  images. In terms of monitoring, I tracked response time, error rate, and latency. This capability helped in identifying performance issues or infrastructure issues before users were impacted. For instance, if Kafka failed, we knew about it before users experienced an impact and could resolve it before it caused maximum damage to our systems. I also used dashboards and alerts to monitor critical services and received notifications whenever issues arose.

The features of Splunk Observability  Cloud that I found most valuable included application performance monitoring and distributed tracing, particularly when monitoring distributed systems or applications. Real-time alerting and Kubernetes  monitoring were essential since Kubernetes is quite complex. I could effectively monitor Kubernetes using Splunk Observability  Cloud. Additionally, the Smart Attack Detector, which I tried at the last moment, was a good feature, although I did not work extensively with it. The Log Observer was very fast and reliable, and the dashboards provided good visualization for troubleshooting and monitoring. If there was a network outage, I received notifications very quickly.

Splunk Observability Cloud helped me detect performance issues faster and reduce downtime in my organization. Earlier, I had limited visibility into my application performance. After implementing observability, I could see end-to-end transaction tracing and quickly identify where issues arose, which reduced troubleshooting time and improved overall application stability and availability for our customers and systems. This capability also helped in proactive detection.

I believe that areas of Splunk Observability Cloud that could be improved include the initial setup and instrumentation costs, which take more time for APM. Some dashboards and detectors require tuning, and I think the visualization needs enhancement. Additionally, alert noise remains an issue, and we need suppressions for when systems go down for short periods. Better integration with third-party tools and easier onboarding of data would also be beneficial.

When evaluating the stability and reliability of Splunk Observability Cloud, I can confirm it has been reliable. I would rate it eight out of ten for reliability.

Splunk Observability Cloud scales very well with the growing needs of my organization. I can demonstrate the scalability of our system to our customers, which is advantageous for business. This capability helped us secure business as we provide real insights to customers who were happy to purchase our systems and applications. The ROI has been good for us.

I communicated with the technical support of Splunk Observability Cloud regarding our issues, specifically when I was unable to monitor or set up Kubernetes to monitor our infrastructure. They were able to help us, and we purchased an on-demand call for assistance, which they provided.

I did not participate significantly during the initial setup and deployment of Splunk Observability Cloud, but I was part of the team. I know the process is straightforward. We simply needed to ensure that all data was in the correct format, matched current dashboard setups, and included all necessary fields for insights.

My experience with lowering the cost of unplanned digital downtime using Splunk Observability Cloud has been positive, as it helped us significantly. Our system was bottlenecking and consuming excessive resources, but with the ability to detect and resolve that issue, overall system usage was reduced without further bottlenecking.

Regarding metrics or data points confirming performance improvement and resilience, I found that during certain times, we experienced the most significant spike in our systems due to multiple users requesting the same service. We needed to change our overall architecture as we were not scaling adequately, and this was bottlenecking our systems. By observing this from the dashboards, I realized improvements could be made. After implementing the solution, our application's stability improved significantly. I can confidently say our availability improved by forty percent, and downtime was reduced by approximately seventy to eighty percent.

My impression of the No-Sample Tracing feature in Splunk Observability Cloud is that it helped us detect key metrics and real use cases, particularly in tracking and monitoring. I primarily tracked server uptime, application response time, API latency, and similar metrics. Combining these parameters instead of relying on a single factor improved our system. Specifically, I used distributed tracing to understand how requests flowed through our network and how different systems responded, which helped determine if any particular system impacted all our systems.

Regarding the AI-powered analytics and guidance provided by Splunk Observability Cloud, I have not actually used the AI features, particularly with ITSI, as I did not utilize that aspect for observability.

My teams effectively utilized the ability to enrich data with custom metrics in Splunk Observability Cloud. They found valuable insights from our systems and created reports that the application and infrastructure teams used to decide their workarounds and solutions. They developed different solutions, experimenting and improving our systems by relying on observability to understand what happens when we adjust parameters or change configurations.

When evaluating the effectiveness of the out-of-the-box customizable dashboards provided by Splunk Observability Cloud, I note that we mostly used the default dashboards. While we created a custom dashboard to track our overall system flow, we relied on pre-built dashboards for monitoring and representing our business perspective. When we needed to showcase our environment to customers, we demonstrated our scalability and system performance, including response time and downtime, providing insightful details from the dashboards for business use cases.

I would rate Splunk Observability Cloud an eight out of ten, where ten is the best and one is the worst.

I work with Splunk Observability Cloud .

Splunk Observability Cloud  is effective for detecting anomalies and preventing system outages.

There are pre-built dashboards where I can check service centers and monitor spikes in errors and traces. I can also check error logs, and everything is consolidated while providing anomaly alerts in case there is any deviation from the baseline.

The personalized dashboard helps my team. Splunk Observability  Cloud has its own query language that can be used to build easy dashboards. Multiple teams can build their own, replicate them, and also have role-based access control, which is beneficial.

The application management feature helps with end-user experiences because front-end monitoring helps track user issues and any back-end issues that may be causing them. It shows how the user experience is overall and identifies any outages. Front-end monitoring is very useful.

As an integrator, I think the biggest advantage of Splunk Observability  Cloud is because it is part of the Splunk ecosystem, it is good to correlate logs with application data through traces and metrics. Overall, it is an evolving product, not top class, but it is getting there.

I see many good things about the product and many advantages. Regarding the negative side, I think the licensing can be much better because it is based upon host units and there is additional licensing for the number of traces that I can bring in. A simplified licensing model would be much better, similar to what other tools offer. Pricing could be either based upon ingestion or directly based upon host units, rather than multiple different trackers. There are licenses for custom metrics, licenses for the number of traces that I can ingest, and host unit licensing. A better licensing plan would be beneficial.

I have been using Splunk Observability Cloud for more than two years.

I have not seen any issues with stability. The solution is very stable.

Regarding scalability, I do not think there is an issue with scaling. I have never encountered any issues with that.

Support is good.

I have worked on Coralogix , which is also an observability tool. I worked in the product company itself. I have also worked on Dynatrace , and now I am working on Cribl .

The installation and deployment process is somewhat challenging, but there are multiple ways of deployment that give me a lot of options. I would say it is acceptable and not that complicated. I can deploy agents with Splunk deployment server, which is beneficial. However, there is some dependency on the deployment server.

As an integrator, I deployed it and made it workable with OpenTelemetry .

I am able to observe significant ROI with Splunk Observability Cloud. When I worked with a previous solution, it was one-third of the cost of Dynatrace , so there was definitely an exceptional return on investment. It helped reduce costs by almost 50%.

Splunk Observability Cloud is affordable. I have visited the PeerSpot  website and downloaded reports on Azure , Grafana , and Splunk Observability Cloud.

When I compare Splunk Observability Cloud to other vendors, the good part is the branding because the support is good. There is a large community where I can look for known issues. However, experience-wise, DataDog is far more superior and easier to use. DataDog has its own agent for tracing, so I just deploy one trace. With Splunk Observability Cloud, they are dependent upon OpenTelemetry , and there is a learning curve because it is open source. The onboarding is not as smooth as DataDog or Dynatrace.

I deploy both on-cloud and on-premise options for clients. I have deployed Splunk Observability Cloud on Splunk Cloud. I have not used threat detection because there is a separate tool for it. I have not deployed a solution on AWS  Cloud or purchased it from AWS Marketplace  in my career. I would rate this review 7.5 out of 10.

My main use case for Splunk Observability Cloud  involves performing visualized performance metrics and tracing capability, making sure that all troubleshooting is faster during incident response. We also integrate it to ensure that every data point and operational data is monitored.

A specific example of how I have used Splunk Observability Cloud  in a real situation is that we make use of it to ensure that every operational data point is being monitored, traceable, and visible.

Regarding my main use case for Splunk Observability Cloud, I would add that we really utilize it in the area of cost management, along with the smarter alerting system and the log search performance.

The dashboard and lead time metrics from Splunk Observability Cloud really improve our workflow, making every workflow more visible and understandable for our stakeholders as well.

Splunk Observability Cloud has positively impacted my organization. Although we have not noticed any specific outcomes, we really recommend it for handling higher data volumes effectively, especially its scalability, which is suitable for us during enterprise environments, monitoring, and alerting.

The best features that Splunk Observability Cloud offers include APM monitoring, the fast alerting system during incident response, and the dashboard that provides real-time metrics.

To improve Splunk Observability Cloud, I wish they could develop more in the area of pricing and cost transparency, provide a smoother learning curve, and enhance the log management experience, ensuring that log navigation is not solely focused on metrics and tracing but also has good search performance to understand larger data sets.

I would also like to see a very good user interface and onboarding experience that is smoother for new users.

Before we wrap up, I want to emphasize the need for improvements in the log search performance and the smarter alerting system.

I have been using Splunk Observability Cloud for over a year.

In my experience, Splunk Observability Cloud is very stable in the area of real-time monitoring and analytics.

When handling higher data volume and scalability, I can say that we have over 70% efficiency now.

For scalability, I would rate it an eight, as it is very good in responding faster and monitoring larger data sets.

We have great feedback from the customer support of Splunk Observability Cloud, as they help solve and make bug alert management easier, respond quickly to incidents, and monitor data sets effectively.

I have not used any different solution before Splunk Observability Cloud.

I have seen a return on investment with Splunk Observability Cloud, with current metrics showing over 75% efficiency. It has really helped our workflow, saved time, reduced costs, and also saved employees' time.

My experience with the pricing, setup cost, and licensing for Splunk Observability Cloud was acceptable at first, though I believe they need to improve more in this area. I would rate it a seven, but overall, the costing and licensing were fine for me.

Before choosing Splunk Observability Cloud, I was recommended to it specifically.

Splunk Observability Cloud deserves an eight out of ten rating. I choose an eight because of their fast response and the monitoring of strong infrastructures.

I would advise others looking into using Splunk Observability Cloud because I am a witness to its effectiveness. It is very beneficial for workflow, making tasks easier and flexible while being able to track and monitor all data sets.

Currently, we are in the process of migrating from on-premises to Splunk Cloud as well as Observability . For metric-based monitoring, we can monitor via Observability  and are migrating it there. We are setting up private locations to monitor synthetic tests, such as ping checks, port checks, and URL monitoring. The rest is metric-based monitoring, which is being done by Splunk using Splunk OTeL, which is an OpenTelemetry  agent for Observability. This agent brings metrics from end devices to Observability. Based on these metrics, we set detectors and rules to trigger alerts.

Our observability is not yet live in production with Splunk Observability Cloud . It is currently being built, and we are adding new components, but it is not yet fully ready.

Comparing to Cloud, Splunk Cloud, or any other solution, the most valuable feature of Splunk Observability Cloud  is that it is entirely based on metrics. The agent is also very lightweight compared to Splunk UF and does not consume much compute resources on the end server or host from which we are pulling data. However, it can only monitor metrics and cannot monitor logs.

Regarding how Splunk Observability Cloud has benefited our organization, we are yet to go live, but most of the configuration that requires conditions and triggers on Splunk Cloud involves writing queries. With Splunk Observability Cloud, the process is quite simple. We can directly get metrics flowing, set thresholds, and everything is UI-based. This requires less time to set up and use. I do not have that much visibility with Splunk Observability Cloud at this time as I am working as an administrator. It has helped us create dashboards for visualization purposes.

There is one thing that could be improved in Splunk Observability Cloud. We have the capability in Splunk to connect to Splunk agents such as Splunk forwarders from a deployment server and update the end agents and forwarders using server classes. We can push and update configurations from our own hosted servers without needing to access the end device. In Splunk Observability, the OTeL agent cannot be updated from our end. Every time we need to update, we have to reach out to users or gain access to the host to update the configurations. There should be a solution to update OTeL agents from Splunk Observability Cloud itself.

I have been working with Splunk Observability Cloud for approximately five to six months.

Splunk Observability Cloud is reliable based on my experience with stability and reliability so far.

We were facing some challenges with the stability of Splunk Observability Cloud regarding the login page. It was not working several times and was not accepting SSO  authentication. The observability team found a solution for this issue, though I am not fully aware of the details. There were several times when opening the page did not directly log in and showed some errors.

I have not encountered any scenarios regarding the scalability of Splunk Observability Cloud. It should be good because it is cloud-based. I am not aware of the licensing model and how it scales or what the rules are for scaling.

I was not directly involved with technical support for Splunk Observability Cloud, but I am aware that my teammates reached out to support. They were finding issues regarding configuration, installation, and deployment of Observability for specific components. Since Observability is cloud-based and hosted by Splunk, the components we own on-premises are the OTeL gateways, agents, and private locations. They reached out to the vendor regarding these components, and the support was quite smooth. They have raised some bugs as well for the vendor to fix. I would rate the technical support from Splunk an eight out of ten.

Since it is cloud-based, Splunk Observability Cloud was ready to use upon deployment. The OTeL gateways were built by our team and required configuration. I was not part of that process but am aware that we needed to configure the OTeL gateways to route data to them as an endpoint and from there it would be ingested to Observability or forwarded to Observability. There were no significant issues with this process and it was quite smooth. However, configuring private locations on a few gateways was quite difficult to set up and maintain because Docker  was going down at times. There were some issues that were discussed with Splunk vendor, and they provided guidance on how to fix them.