Splunk Observability Cloud Reviews

My main use cases for Splunk Observability Cloud include Application Performance Monitoring, synthetic monitoring, and dabbling in infrastructure and what comes along with it; however, we do already have a tool that does infrastructure. We're debating about just switching it all over to Observability.

The features of Splunk Observability Cloud that I prefer the most are its all-encompassing licensing model, which is comparatively better than others in the market. We're switching off AppDynamics, and the licensing model always constrained us, so that is our main reason for switching to observability, as the licensing is all-encompassing.

The benefits of these features for my organization are significant. The license is all in one, meaning infrastructure, APM, synthetics, RUM, and the logs are all under one license, allowing us to offer that to our application teams more so than we were ever able to do before. 

We're currently trying to implement RUM, Real User Monitoring, with two applications just to get a feel for it, which we were never able to do before, since it was a completely separate license that we needed to purchase. So we're able to offer more of a full suite, more of a one-stop shop sort of thing, versus what we were able to do before.

The user interface of Splunk Observability Cloud needs a lot of work. I have been known to describe it as slapping lipstick on a pig. The pretty colors draw in everybody, however, the actual functionality of it has a lot that you cannot do, and how the user interface is organized is very difficult to navigate. This is a driving factor for us not to use the product.

The next release of Splunk Observability Cloud should include a feature that makes it so that when looking at charts and dashboards, and also looking at one environment regardless of the product feature that you're in, APM, infrastructure, RUM, the environment that is chosen in the first location when you sign into Splunk Observability Cloud needs to stay persistent all the way through. There's no reason that a user should have to keep having to restart all of their filters and select their environment anytime that they switch to a different area of the tool.

I have been using Splunk Observability Cloud for one year exactly.

I have not experienced downtime, crashes, or performance issues with Splunk Observability Cloud yet.

Splunk Observability Cloud scales with the growing needs of my organization, however, we very quickly always run into hitting the limit for custom metrics. This is something we've discovered that we have to manually manage, which is not fun, especially for large applications such as our huge tracking system, since we're a logistics company, as well as the two main revenue-generating applications. We are probably going to hold off putting them into Splunk Observability as we're constantly bumping the limit already.

I would evaluate customer service and technical support as hit or miss as I get the impression that the support folks assigned to our account might be spread a little too thin. They are good people and do good work; however, I get the impression they're spread a little too thin. If we put in a ticket, we do get a response in a decent amount of time, so that's not a problem.

Positive

Prior to adopting Splunk Observability Cloud, I used several solutions. The solutions we used include Zabbix, Splunk Core, Grafana, Prometheus, and AppDynamics, so a whole suite of things.

The deployment has been fine for cloud applications. It is very tumultuous for on-prem. That is supposed to be getting fixed over the next year. Right now, it's not there. So I always tell my management we're a year and a half too early for this tool.

I have seen ROI for our cloud applications, as we've been able to fully integrate with one application, which is a big revenue producer for the post office, and it's something that they were not able to do before, so we have been able to see that. In terms of ROI, I would say 100%.

We don't currently use the out-of-the-box customizable dashboards provided by Splunk Observability Cloud to showcase IT performance to business leaders. 

I will say we have not expanded usage to other applications since we're still stuck where we are. 

My advice to other organizations considering Splunk Observability Cloud is to wait until next year. 

On a scale of one to ten, I would rate this solution five or six.

My main use case for Splunk Observability Cloud is application monitoring.

The features of Splunk Observability Cloud that I appreciate the most are ops intel and the community support. These features have benefited my organization because they help us find the root cause of any issue quickly and pinpoint the exact location where the issue exists.

We have not yet completely gone into production, so I do not have any metrics or data points to share. To evaluate the effectiveness of Splunk Observability Cloud in improving digital resilience within my organization, we have various client applications, such as the teller application and our online banking applications. 

Initially, before Splunk, we had a long time to resolve issues. Now, with Splunk Observability Cloud, we will be able to solve them quickly and know exactly where the issue is. Previously, we needed to go to the war room to find where the issue was. Now, with Splunk Observability Cloud and all its agents and data, we know exactly where the issue is located.

Regarding the no-sample tracing feature, all the data fed by the agents to Splunk Observability Cloud means we do not have to worry about missing any issues during sampling. We have not yet explored the AI-powered analytics feature, but we have partially explored MLTK.

My teams have utilized the ability to enrich data with custom metrics by writing custom agents in Java and Python to collect those custom metrics and feed them into Splunk Observability Cloud. This is particularly useful for applications without direct Splunk agents.

The out-of-the-box customizable dashboards are helpful in showcasing IT performance to business leaders. They provide guidance on requirements we may not have visualized and help us build custom dashboards to include our company-specific metrics. We have not yet expanded usage since we haven't started using it extensively.

To improve Splunk Observability Cloud, we need more applications to be included in the observability so that more applications can have agents to monitor them and bring that information to the cloud. 

Splunk Observability Cloud has not yet completely improved our operational performance for our company's resilience as we are just starting out, however, it will help us ultimately to reduce incident time.

I have been using Splunk Observability Cloud for one year now.

In my experience until now, I have not experienced any stability issues with Splunk Observability Cloud.

Splunk Observability Cloud scales effectively with the growing needs of my organization. As we are a growing company transitioning all our applications to the cloud, and with the increasing number of cloud-native applications, Splunk Observability Cloud will help us achieve digital resiliency and reduce our mean time to resolution.

I would evaluate customer service and technical support as excellent, as Splunk has been quite responsive to our service requests, with their team providing good support.

Positive

Prior to adopting Splunk Observability Cloud, we were using Splunk Enterprise, and we had custom monitoring tools developed in-house.

The installation of Splunk Observability Cloud worked smoothly once we figured out the initial issues. The agents do not consume many resources, and the type of metrics they collect is helpful.

Since we have not progressed far into the implementation of Splunk Observability Cloud, I cannot comment on the return on investment at this time.

I am not involved in the experience with pricing, setup cost, and licensing.

I rate Splunk Observability Cloud eight out of ten.

My main use case for Splunk Observability Cloud is end-to-end tracing of business processes.

Splunk Observability Cloud has helped improve my operational performance and my company's resilience.

What I appreciate most about Splunk Observability Cloud is the correlation feature, specifically the ease of correlating logs and issues to those traces to see where within the path of the business function is failing. 

One significant way these features benefit my organization is through mean time to resolution. Taking away that first instinct of where we're trying to figure out what's wrong will drop that time significantly, so rather than a few hours, potentially we're looking at a few minutes before we can start resolving an issue.

In terms of operation performance and resilience, I have experienced improvements in mean time to resolution and the ability to detect issues that we weren't detecting ahead of time. I can give a specific case scenario; while we were in a POC situation, it was able to find issues we were having with servers just by random chance. We implemented it and it happened to let us know about an issue before our NOC even knew that it was occurring.

My teams have utilized the ability to enrich data with custom metrics in Splunk Observability Cloud during the implementation process, and we're definitely seeing a huge difference in what data we have, and the teams are extremely excited by the new amount of data we're getting in. I find the out-of-the-box customizable dashboards provided by Splunk Observability Cloud extremely beneficial since they give you a lot of information already, and the ability to customize and do your own is even better.

I ran into a small security incident. Splunk Observability Cloud was able to help us with that along with Splunk's core process or core offering. Between the two, we were able to use it for correlations, which helped with mean time to resolution and getting us back up and running much faster.

Splunk Observability Cloud could be improved with better integration with AppDynamics, as we know that's coming, however, it is an issue we've had between the OpenTelemetry and the AppDynamics collector. We saw a complete difference in what data was being brought in, however, we know that issue is being resolved and that's a big one for us.

I would assess the stability and reliability of Splunk Observability Cloud as okay. We've been experiencing an issue with the cloud console, and we're working with support to get through that. We're assuming it's just a growing pain at this point. Particularly what we're having is disconnection from the cloud console, where we will be working in it and receive a message saying that we've been disconnected and have to wait for it to come up. It's been painful and seems to be a new issue, and they're trying to figure out what's going on,however, I haven't heard of anybody else having that issue.

Splunk Observability Cloud seems to be scaling quite well with the growing needs of my organization.

I would evaluate the customer service and technical support for Splunk Observability Cloud as fantastic. On a scale of 1 to 10, the customer service and technical support deserve a 10.

Positive

I have seen a return on investment with Splunk Observability Cloud.

I would advise other organizations considering Splunk Observability Cloud to definitely POC it to see if it's going to work for their situation. It may not be for everybody. That said, definitely give it a chance and see what it can do for you and the kinds of new information it can bring in for you.

On a scale of one to ten, I rate Splunk Observability Cloud nine.

I am using Splunk Observability Cloud as a log-based monitoring tool for my databases. We have ingested our database logs and OS system logs into Splunk Observability Cloud and are creating dashboards and alerting features over those alerts. One of my major use cases is that all kinds of databases I am currently working with have database logs that capture all information, warnings, and error messages. These database logs are moving to Splunk Observability Cloud. The first use case is that I no longer need to maintain a long list of flat files on my server for all those logs. Those can be directly ingested into Splunk Observability Cloud. The benefit I am seeing from here is that I can get pattern-based analysis of what kind of errors I am commonly getting and what the date patterns of those errors are. I can get dashboards over that and I can also create alerts. I can also incorporate those alerts with some back-end Git workflow for automatic remediation. This is one of the solutions.

Another use case for Splunk Observability Cloud that we are seeing is that there are multiple times when there is a requirement to publish some kind of data. So instead of publishing an alert if those data breaches occur or if some kind of dashboard needs to be created, instead of sending data directly to the users, if that data is not PII, we are also ingesting that into Splunk Observability Cloud in a JSON format and then again, dashboards and other alerting can be created. These two are the main major use cases for which I am using Splunk Observability Cloud.

With the help of the alerting and observability mechanism, resiliency, and automatic automation of issue remediation based on alerts and workflows, it actually reduces the cost and increases the uptime of my system and customer satisfaction. There are multiple indirect benefits I am getting when using Splunk Observability Cloud.

Currently, with the growth of the organization, I am seeing an increasing use of Splunk Observability Cloud in a more dynamic way. We are continuously creating new dashboards, ingesting logs in JSON, and trying to bring the best value out of it. I am seeing a dynamic and drastic increase in the use of Splunk logs and the Splunk data we are ingesting.

There are two aspects to expanding the usage. Organic growth of the environment actually puts new systems into Splunk Observability Cloud, and exploring new opportunities for what all can also be ingested into Splunk Observability Cloud. Previously, I can see that memory dumps are there. We are also looking at whether we can ingest memory dumps so that if the system is about to crash, those memory dumps can be captured into Splunk Observability Cloud so that it can create alerts over that and I can also perform analysis. I can also see if any other system is facing the same kind of memory dump issues. So that maybe it is one alert for one system for me, but for the complete farm, there may be different servers with different teams or business units facing the same issues. When I have Splunk Observability Cloud on all systems, I can actually create a consolidated report and see that this is the pattern which particular farms are having this kind of issues, and maybe something is broken. This is the way the plan is to increase the availability or the usage of Splunk Observability Cloud.

The performance and speed are valuable. Previously when Splunk offered the enterprise solution, I needed to install Splunk and maintain my local server. There was a limitation that only a certain number of servers could be supported in one instance and I would need to have multiple instances if I was in an enterprise system setup. When I am in the cloud, a single instance can support N number of systems. It is pretty fast, no matter how much data is there. Dashboards are pretty good with multiple functions available. The alignment or integration that can trigger automatic solutions with the workflow for automatic remediation of the alerts is the best thing. These three or four things are the best Splunk Observability Cloud features that I am seeing.

The point in time alerting, the point in time data capture, and automatic remediation with the integration of good workflows or Ansible workflows is definitely the key to any resiliency and increasing the uptime of any system.

After moving to Splunk Observability Cloud, it is almost zero downtime. We never face downtime because when I was in the enterprise setup, I needed to maintain my servers and maintain hygiene of vulnerabilities, patches, and all. Now when I am in the cloud, everything is automatic. Almost zero downtime plus the perfect alerting feature and log-based analysis are available. Metrics alerting is also there in Splunk Observability Cloud through queries. This is one of the features that keeps me updated with the current health of my system and helps me to keep my system up and running fine and available for my customers.

Splunk Observability Cloud incorporated a new AI agent feature that is really good. Sometimes I need to create queries and Splunk queries for filtering the data and some pattern-based analysis. This agent is really good in helping me and suggesting the queries. This means I do not need to have a Splunk expert or Splunk query expert. I can just ask that agent that I need pattern-based analysis or I need to create this kind of filters for this kind of data and it can suggest to me. Once it suggests a sample query to me, I can do the tweaking and I can have my data ready. It actually reduces my time to perform my analysis and to reach the conclusion about what exactly is causing issues in my system and what are the repetitive issues in my system. This AI feature really helps for newcomers to Splunk Observability Cloud to perform deep diving analysis with the data captured by it.

Custom metrics are valuable. In Splunk Observability Cloud, some infra-level metrics are not available, but through custom metrics, I can achieve it. This is an add-on feature that Splunk Observability Cloud is providing and without any additional monitoring tool. If that feature was not there, then I would need to plan some other monitoring tool for metrics-based alerting, but this custom one helps me to achieve it in the same monitoring tool. The consolidation and integration of metrics-based alerting and log-based alerting in a single tool is actually the lovable feature. I do not need to worry about or look for multiple tools. I can have my own data and own health available in a single tool, in a single view.

The dashboards are good, but the only limitation I see currently is that they need particular formats only to create a dashboard. They need to have a particular JSON format or time series format. This sometimes creates additional work for me so that when I am ingesting logs in Splunk Observability Cloud, it should be in a specific format. Either Splunk Observability Cloud should have multiple formats available or multiple dashboards available for different kinds of formats. At least Splunk Observability Cloud has everything available at a Splunk level. They can do some kind of analysis and see what are the major top ten or top twenty types of logs they are getting and they can have dashboards according to those logs. Instead of forcing customers to design their logs in the way of Splunk Observability Cloud, Splunk Observability Cloud can create dashboards based on the customer requirement. This will actually ease things up for the end users.

The current dashboards are good. The feedback is that Splunk Observability Cloud is forcing me to modify my logs that I am ingesting in Splunk Observability Cloud in a specific format. If Splunk Observability Cloud can leverage it and make it open for any format, that would be great. If that is not feasible, at least the top ten or top twenty logs that Splunk Observability Cloud is getting should be readable by Splunk Observability Cloud without any changes. That actually is one of the major feedback items I can provide which can actually ease the life of the end users or any layman. As a newcomer to Splunk Observability Cloud, I may not know JSON. I now need to hire someone or I need to look for someone who knows JSON and who can convert my logs into JSON format and then I will ingest them into the logs if I want to create a dashboard. If I do not want to create a dashboard, that is okay. On the other hand, Splunk Observability Cloud is giving me a usability and easy to go interface, but for a dashboard, I need to have an understanding of JSON so that I can ingest the log in JSON format. That is a dilemma that they have and they should work on.

Currently, Splunk Observability Cloud is not the only solution which any organization is using. There is also Grafana and PagerDuty. If Splunk Observability Cloud can plan some kind of integration with PagerDuty and Grafana, then those things can be controlled from a single position and if something else is happening at one location, it can update things at all levels. That can also bring great value to the users. Currently, I have to maintain three systems separately, but if some kind of integrations can be developed with these three vendors, then that can be a great thing because all these three have now become the industry pillars or industry standards for observability and resiliency.

I have been working with it for the last two years. Before that, it was an enterprise solution. Now it is cloud-based.

I cannot relate any stability issues to my experience with Splunk Observability Cloud.

Scalability is pretty smooth. I just need to deploy the Splunk forwarder and the config file that specifies which servers it should connect to and it will get connected. My data will start populating. It is pretty straightforward. I do not see any challenges there, even when it was in enterprise and now when it is in the cloud. The deployment and onboarding of new servers and ingesting the logs is pretty straightforward. Anybody can learn it within a day without having any prior knowledge.

We have raised multiple questions when we face any issues. Our support is prompt and usually within a day, I will get my answers.

Positive

Previously I was on Splunk Enterprise. I have been using Splunk for seven to eight years before we moved to the cloud in the last eighteen months.

The initial setup is pretty smooth. I just need to deploy the Splunk forwarder and the config file that specifies which servers it should connect to and it will get connected. My data will start populating. It is pretty straightforward. I do not see any challenges there, even when it was in enterprise and now when it is in the cloud. The deployment and onboarding of new servers and ingesting the logs is pretty straightforward. Anybody can learn it within a day without having any prior knowledge.

I appreciate that your organization collects reviews about the product so that it can be shared with the vendor or the product owner as appreciation or as feedback for improvement. Everything has been smooth in my experience. I would rate this product a ten out of ten.

My main use cases for Splunk Observability Cloud include retail analytics.

The feature I appreciate the most about Splunk Observability Cloud is Synthetic Monitoring. These features have benefited my organization by increasing availability and decreasing downtime, providing assurance that makes you feel good, and ultimately enhancing well-being.

The out-of-the-box customizable dashboards are very effective. At the same time, we also use Splunk Cloud to enhance them. The Splunk Cloud is a better dashboarding experience.

Our teams have utilized the ability to enrich data with custom metrics in Splunk Observability Cloud. We've been doing a lot of that with event management and linking that into IT as well. So we're using that to be able to tie systems together. The integration we have between Observability Cloud and ITSI for event management is where we're using that type of stuff.

Splunk Observability Cloud could be improved by having more integration with Splunk Cloud because at the moment they're two separate products. They're making great moves on what they call unified access; tighter integration is always a good thing.

I have been using Splunk Observability Cloud for three years.

I would assess the stability and reliability of Splunk Observability Cloud as generally good. We have experienced the odd bug; however, nothing too serious, and Splunk has been quite good in terms of resolving issues; it's just routine stuff and nothing bad.

Splunk Observability Cloud scales incredibly with the growing needs of my organization. It just means the more we use it, the more expensive it is, but there are no issues reported.

I would evaluate customer service and technical support as fantastic; nobody is better.

Positive

During the deployment, we only had some challenges when we switched on unified access. However, they were just teething problems.

I have seen a return on investment with Splunk Observability Cloud as we have averted some things that may otherwise have resulted in downtime. We have had it avert potential problems, and the first time it happens is a return on investment. The second time, nobody notices, making measuring business value a challenge.

I would advise other organizations considering this solution to give careful attention to the use cases they have and how they plan to proceed in terms of their roadmap over the next two to three years, as there are alternatives. Having an idea of where you want to go will help you make a better-informed decision.

Additionally, it's good advice to have a customer reference call to learn from someone's experience and avoid pitfalls.

On a scale of one to ten, I would rate Splunk Observability Cloud overall as a good eight; as soon as it's all integrated neatly together, then it's up in the high numbers.

I use Splunk Observability Cloud for network logging analysis.

I prefer the dashboard building and search features of Splunk Observability Cloud the most. Splunk Observability Cloud has helped improve my operational performance. 

Previously, we used Elastic for similar purposes as Splunk Observability Cloud, and this has allowed us much more visibility into what we're working on with usable dashboards and metrics, which has been awesome.

The only strain point we've encountered with Splunk Observability Cloud is that the search times can be lengthy for some things. We have a large environment, so that's expected. That's the only complaint I've had so far.

I have been using Splunk Observability Cloud for approximately three months.

I experience slow searches occasionally with Splunk Observability Cloud, but there are no outages or anything in that regard, so it is pretty stable and reliable.

Splunk Observability Cloud scales with the growing needs of my organization effectively. As a large organization, we find it impressive that our volume has been handled with only occasional slow searches.

I haven't worked with customer service and technical support directly, however, another engineer on the team has shared positive feedback about their experiences.

Positive

Prior to adopting Splunk Observability Cloud, I was using Elastic. Support was a significant factor that led to switching to Splunk Observability Cloud. The previous solution wasn't fully supported by their team, and there weren't adequate integrations or visibility needed for some of our applications. Additionally, it was a legacy installation set up by former employees, so this was an opportunity to start fresh with people who are actively involved.

We haven't had Splunk Observability Cloud long enough for me to make substantial comments on its effectiveness in improving digital resilience within my organization.

I wasn't involved in the licensing. 

We haven't used the no-sample tracing feature in Splunk Observability Cloud specifically for eliminating blind spots in data collection. We haven't implemented the AI-powered analytics and guidance features provided by Splunk Observability Cloud either.

Our main security architect has done extensive work utilizing the ability to enrich data with custom metrics in Splunk Observability Cloud by setting up specialized dashboards and searches for our various integrated apps, including ISE and Palo firewall logging.

I haven't extensively used the out-of-the-box customizable dashboards provided by Splunk Observability Cloud as we're still using our custom ones. I wasn't involved in the pricing, setup, cost, and licensing. I enjoy using Splunk Observability Cloud, but I'm not familiar with the cost aspects.

Access to Splunk Observability Cloud has been reliable for all users. On a scale of one to ten, I rate Splunk Observability Cloud an eight. 

I recommend spending time working on your own dashboards and searches to fit your business needs, as that's where you'll get the most value out of Splunk Observability Cloud.

We are using the Splunk Observability Cloud for monitoring purposes and troubleshooting, and we are using that infrastructure in real time, in which we have infrastructure monitoring, application monitoring, log observer, and RUM synthetic monitoring. For troubleshooting purposes, we are installing the open telemetry collector agent on some of the servers, including Intel, Windows, and UNIX servers. 

I have also worked on the agent upgrade from version 0.103 to 0.1113, which is ongoing right now.

We are also using the dashboards and detectors in Splunk Observability Cloud. For client needs, we are creating dashboards, reports, and detectors as well. For the detectors, we mostly work on host-down situations. When a server is down, we troubleshoot using the detector infra host down and identify the root cause of the failure, such as why it was down or not reporting to Splunk Observability Cloud. We find out the root cause by using that detector when the alert gets triggered and cleared.

We use the tracing features in the Splunk Observability Cloud, primarily for application performance monitoring. It helps us figure out service maps for root cause analysis. It provides visibility and helps address blind spots in data collection.

Splunk Observability Cloud offers a transparent, customized tool with real-time visibility. We use AWS, ReactJS, Python, and Java for tracing. It helps create customized dashboards and service maps based on customer requirements. It has AI that automatically generates visualizations, allowing us to create more reports based on customer needs. My seniors are primarily working on creating dashboards, reports, and for monitoring purposes.

Their technical team is performing well. About a year ago, Splunk Observability Cloud was slow and lacked features compared to now. It didn't provide exact details for any searched server in the metrics, but the situation has improved significantly, and we can now retrieve complete data on when servers were down or up.

The best features in Splunk Observability Cloud are the metrics; I can see any logs or anything related to the server or services we want to monitor, and the metrics are a good function. It provides exact details. It offers unified visibility for logs, metrics, and traces.

In Splunk Observability Cloud, I notice room for improvement in synthetic monitoring. It does not provide output based on server names. It only gives a response when we input a URL. I'm not sure if this issue is specific to my organization, but it would be beneficial if server details could be retrieved directly in synthetic monitoring.

I have been using this solution for two years and two months.

I would rate its stability an eight out of ten.

I would rate its scalability an eight out of ten.

Around 100+ users access Splunk Observability Cloud in my organization, including the cloud SRE team, Windows Intel team, Linux team, and AD team.

My client base primarily consists of enterprise financial services.

If any issues arise, we can raise a vendor case, and resolutions are provided in a timely and accurate manner. 

Positive

In my organization, we also work with Sentry, Datadog, PagerDuty, and Dynatrace. Splunk Observability Cloud offers more features than Datadog, which also provides APM monitoring, log observer, and metrics, but does not match the feature set of Splunk Observability Cloud.

It is a bit complicated. For deploying Splunk Observability Cloud, we first need an access token, after which we connect to our AWS Cloud account and provide the access token. We must set up CloudWatch or AWS Lambda and forward the metrics or logs from all sources to AWS.

The implementation took about 45 days.

The return on investment varies based on requirements; for smaller tasks, we can leverage our team's capabilities effectively, so I can estimate around a 20% efficiency gain.

Currently, we are providing outputs to clients within the required time frames. If a client requests any dashboard, logs, APM monitoring, or synthetic monitoring, we have been able to deliver output on time, achieving approximately an 80% efficiency in response.

Splunk Observability Cloud is expensive.

For operational performance, we created monitoring within the Splunk Observability Cloud for most servers with agent installation. We upgraded the open telemetry collector from version 0.82 to 0.103, then again to a newer version, enhancing visibility and use cases, especially after the upgrade, which has improved operational purposes.

My impressions of Splunk Observability Cloud for focusing on business-critical initiatives are positive. I manage six tools, but Splunk Observability Cloud is one of my favorites, and I aspire to build my career specializing in it because it has great features, more attention in the market, and is a relatively new tool with promising growth.

I would recommend Splunk Observability Cloud to other users for its accurate data fetching, dashboard creation, report generation, and synthetic monitoring capabilities.

I would rate Splunk Observability Cloud a nine out of ten.

Our main use cases for Splunk Observability Cloud are to observe our application, our websites, and our infrastructure metrics.

What I appreciate the most about Splunk Observability Cloud is the APM part and the log analytics part. These features can help us with troubleshooting our problems between multiple systems. 

Distributed tracing is very useful to us, and the infrastructure part can help us identify problems with the infrastructure. Splunk Observability Cloud has helped improve our operational performance and our company's resilience on the path of adopting it, and I expect more improvements in the future.

The RUM part of Splunk Observability Cloud can be improved significantly. We are currently struggling to use it since our application is mixed mobile and non-mobile. Some AI features in the search functionality could be beneficial in the next release of Splunk Observability Cloud.

In GCP, Cloud Run is not natively supported by Splunk, and we are challenged with bringing data from Cloud Run to Splunk. Native support of it in the future would be great for us.

We started using Splunk Observability Cloud one year ago.

I would assess Splunk Observability Cloud as quite reliable. The only problem is the graphical interface, which sometimes is buggy. It crashes, doesn't display data, and requires reloading the browser. I have experienced downtime with Splunk Observability Cloud only once, which lasted one hour due to issues that prevented us from logging into the platform.

Splunk Observability Cloud scales with the growing needs of our organization quite efficiently. I have expanded the usage of Splunk Observability Cloud, and the process of expanding usage was smooth apart from one part.

Customer service and technical support respond very quickly. That said, sometimes the solutions take too long to implement.

Neutral

Before adopting Splunk Observability Cloud, we used DataDog, and before that, we had no solution. The factors that led me to consider the change were mainly because my company has different IT offices. My IT office used DataDog, another IT office used New Relic, and others used different tools. We needed to adopt Splunk across the group to have something standard in my company.

My experience with deploying Splunk Observability Cloud was quite good, mainly since we almost have everything on cloud and that makes deployment quite easy.

My advice to other organizations considering Splunk Observability Cloud is to adopt it if you don't have anything else as it's a very good tool, and having something for observability is very good. Not only for the observability part but for all the Splunk platform, that's great. 

On a scale of one to ten, I rate Splunk Observability Cloud a seven out of ten.