Splunk Observability Cloud Reviews

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.

Our main use cases include synthetic monitoring, APM, RUM, alerting, detectors, dashboards, and all related functionality.

My favorite feature of Splunk Observability Cloud is the RUM because I like the RUM data. Splunk Observability Cloud has helped improve our operational performance and company's resilience, which was their initial offering. Without it, we wouldn't have any exposure and would be looking at raw data.

It can be improved through the integration of AI, which is either coming or already available.

I've been using Splunk Observability Cloud for two and a half years.

I've only experienced downtime, crashes, or performance issues when it isn't configured correctly.

Splunk Observability Cloud scales effectively with the growing needs of our organization; we simply need to pay more and ingest more data.

Prior to this, I wasn't using another solution to address similar needs.

I've seen ROI with Splunk Observability Cloud, though I cannot specify the exact amount. We would be unable to track user access issues without it, which would result in significant losses.

I use the cloud almost exclusively and am still learning some features. I handle synthetic monitoring, but don't manage all integrations or usage aspects. I need to explore the AI-powered analytics and guidance, as we haven't implemented it yet. The out-of-the-box customizable dashboards are effective because they contain all the necessary base components.

On a scale of one to 10, I would rate Splunk Observability Cloud as an eight. I appreciate the cloud because it provides more visibility into the user's path. It's quite good, though the observability aspect is somewhat complicated, primarily due to my limited experience with it.

The use cases for Splunk Real User Monitoring (RUM) are almost the same as Dynatrace, for people who want to do infrastructure monitoring, application monitoring, or check their front-end monitoring, such as monitoring for the real user. They are actually using Splunk Real User Monitoring (RUM).

The best advantages and features in the product are notable. Splunk Real User Monitoring (RUM) seemed to have advantages in 2015, but when Cisco acquired AppDynamics, they stopped upgrading for a few years. Their advantage now is that they are the only solution that can monitor above SAP. Apart from that, Datadog and Dynatrace have superior features. Splunk Real User Monitoring (RUM) has one great advantage in that if they have SAP users, they can monitor their SAP applications.

In terms of features, UI, or the ability to do monitoring of RUM, the picture by UI or the ability to actually do the monitoring is pretty good, but not as good as Dynatrace, Catchpoint, Datadog, and New Relic.

My thoughts on room for improvement in general relate to Cisco trying to mount the Cisco cloud solution when they have AppDynamics, but after acquiring Splunk, they changed their roadmap. It's inevitable that when a big company has resources but changes the roadmap, it takes time to establish well-structured manuals and guidelines. I believe they will get better, but right now, they need some improvement.

I have been selling Splunk Real User Monitoring (RUM) for almost the same duration as NetScout; it's been 3 years.

In terms of deployment, Dynatrace is the easiest by far. For Datadog and Splunk Real User Monitoring (RUM), you have to work with scripts, meaning you need an engineer for deployment; Dynatrace is straightforward and really easy.

Regarding stability of RUM, stability is also a problem because during the POC, we ask customers not to deploy RUM or EUM scripts in the actual stage. We encourage them to test in staging because even if those solutions are certified and tested, customers have many different environments. Unlike NetScout or regular agents for APM, RUM has many problems during the POC phase because customer environments vary widely.

In terms of scalability, the solution is scalable enough, but sometimes implementation is hard. However, it doesn't take more than a month. The issue is mainly about pricing because if they want to monitor more, it costs money. Those who have a great pricing plan or volume table will gain an advantage.

Support from Splunk is not very helpful because Splunk doesn't have a dedicated APM; they only have one APM engineer in Korea.

If I were to rate technical support for Splunk Real User Monitoring (RUM) from 1 to 10 points, I would give it a score of 5.5. I appreciate the engineer, but since there's only one person doing everything, it's not easy. Cisco doesn't hire enough personnel, and I heard they don't have enough staff in APAC. Datadog and Dynatrace, especially Datadog, cover a huge market share in Asia, and that's why other competitors are not investing enough at this time.

Neutral

My clients, such as Hyundai and POSCO, are using RUM; most of them use Dynatrace. For those using Splunk Real User Monitoring (RUM), it took time to implement because our engineer tried really hard.

Regarding whether the solution provides ROI or savings, I understand that even Dynatrace, Datadog, or Splunk has a low price per transaction, but it concerns the number of data and sessions. People struggle to comprehend the total budget, which might be massive. Customers need to understand this, and I'm not sure if it's possible; maybe some companies just decided to take the entire market and cut down prices, but anyone working in front-end management should recognize the market price to see the true value of end-user monitoring.

I am the general manager of this company, and a team leader focusing on Dynatrace, Cisco AppDynamics, and NetScout, while we used to do some other APM solutions but not extensively. We only focus on those three solutions.

We try to sell Splunk User Behavior Analytics, but we haven't been able to sell it so far because Splunk used to be a great company in Korea. After Cisco acquired it, it's complicated because when two companies merge together, they have issues with who will be the product seller, the sales personnel or the engineer. Their organization is not fully merged yet, which leads to fewer marketing and sales activities.

The integration in real user monitoring from Splunk is actually another problem because of some vacancies when they merged the companies and changed the organizations; there are issues with the manual not being complete. When you work with integration, Datadog and Dynatrace have issues but have to work with the manual; AppDynamics has many people and support. The satisfaction level is around six compared to Dynatrace, which might be a seven or eight. The innovation level is not complete, but they are working on it.

When using real user monitoring to analyze performance bottlenecks, the most critical metrics include data from Catchpoint, which has extensive data to gather, and Dynatrace also gathers substantial data. However, sometimes it's unnecessary because customers in charge of front-end monitoring should see the problems immediately and act with reporting to their superior. A simple UI is crucial; that's perhaps why Datadog has the advantage with their comprehensive UI.

Regarding pricing for RUM, it becomes another problem because Splunk and Dynatrace and Datadog don't ask customers to use RUM for every single session. Many large customers want to monitor every session, resulting in a big gap. For example, Korean Air, which is among the top five air travel companies in the world, uses Datadog but changed to Dynatrace because, even with a limited budget, Dynatrace managed to persuade them to monitor just 10% of user sessions to reduce the budget, and they are satisfied with the results.

This review rates Splunk Real User Monitoring (RUM) 5 out of 10.

Splunk Observability Cloud's main use case for my organization is related to infrastructure monitoring, application monitoring, synthetic monitoring, and detection across all of them, while simultaneously gearing up for real user monitoring.

In my day-to-day work, I develop different sorts of dashboards across Splunk Observability Cloud, build different sorts of synthetic test detectors and alerting criteria for different requirements and KPIs, and occasionally onboard new agents and collectors over Splunk Observability Cloud. It covers everything.

The best features I have observed with Splunk Observability Cloud are the Splunk AI Observability AI assistant, which is very helpful, and the recently added AI troubleshooting for APM-related metrics. Detectors and active alerts are very helpful as well.

I am really excited to see the new fleet management, which I have been exploring initially. Fleet management would make a bigger difference since it allows us to control and manage YAMLs across all agents, and if remote upgrades become available in the future, that will be really helpful.

It has positively impacted my organization in terms of observing different sorts of metrics and tracing across different applications, and it is really helpful.

Many of the fleet management features are still not as updated as required, and I am looking forward to those improvements. Some of the Oracle DB configuration is still not very easily configurable currently, which requires more attention.

The agentic observability and AI observability look very promising based on what I observed in the keynotes, and I am looking forward to all these changes. Once available, I think we will be able to add more capabilities to our implementation.

I have been using Splunk Observability Cloud for the past three years, and I started working on it when it was on version 0.86. I have been working with the recent version of .160 and have deployed all of the recent versions in the past.

There are some issues sometimes, especially with the US zero realms, for which the team is responsive. However, there are recurring issues with the US zero realm, so I think it requires more stability.

I am hoping that after having fleet management, scaling would be comparatively easier. There are still dependencies across different teams for scaling purposes, so I am looking forward to fleet management for the same. I think it is improving.

Customer support is good.

Splunk Observability Cloud is a good product and one of the major products when it comes to observability. They provide us with a better template to prepare. I would rate this review an 8 out of 10.

My primary use cases for Splunk Observability Cloud include creating dashboards for metrics, detecting incidents, and ensuring overall observability of applications, service connections, and integrations, along with reporting and Slack integrations.

By visualizing the integration of the service, I can understand the flow of the data, which is one of the features I appreciate most about Splunk Observability Cloud.

With the metrics collection, I can proactively find incidents and work on the major issues when they happen and predict these issues.

With alerting and the detectors, we can inform the engineers that are on call to take over the service responsibility.

With the metrics and the dashboards, we can have a clear view of how the system is performing. Splunk Observability Cloud has helped improve my operational performance by detecting, analyzing tracings, and detecting alerts.

50% of our metrics on Splunk Observability Cloud are custom metrics, so we heavily rely on that. The out-of-the-box customizable dashboards provided by Splunk Observability Cloud are excellent, especially with the Amazon ones, AWS, memory cache, and Kubernetes dashboards, which are complete for the Kubernetes needs.

The UI of Splunk Observability Cloud is one of the major issues; it's old and has been there for more than 10 years, acquired by other applications from other companies. It's time to reinvent how the UI is going to work with the AI modules and integrations, making it softer and cleaner.

Splunk Observability Cloud is comprehensive in terms of functionality and features, so educating users has to be more functional. Users need to know how to be educated about certain views or pages they're working on.

I have been using Splunk Observability Cloud for five years.

I assess the stability and reliability of Splunk Observability Cloud as built on top of reliability because of the Cisco networking and infrastructure. That's not a concern for me; I totally rely on it. I've experienced downtime, crashes, and performance issues with Splunk Observability Cloud, as with any other solution. Comparing it with other monitoring solutions, Splunk has been excellent with availability. When I experienced issues, they were communicated through maintenance windows, resulting in 100% satisfaction with how they conduct this.

Splunk Observability Cloud scales very well with the growing needs of my organization. We didn't have scaling issues as the application evolved. I expanded usage of Splunk Observability Cloud when the company opened new coverage areas in different countries. Adding those metrics or new indexes to Splunk wasn't much of an issue in scaling.

I evaluate customer service and technical support for Splunk Observability Cloud as having only great experiences working with people at Splunk.

Positive

Prior to adopting Splunk Observability Cloud, I was using Datadog, which would accomplish 70% of what Splunk does currently.

There have been so many challenges that I can't name one right now. There is always a challenge in deploying open source material, like the open telemetry modules, that don't have the reliance on Splunk. It's just an integration challenge that we have the most. Deploying Splunk itself wasn't that much of a big deal.

I see ROI with Splunk Observability Cloud. My company is heavily dedicated to analytics, so the Splunk deal is significant. I cannot imagine how the business would run without it currently.

I had low pricing and setup costs for Splunk Observability Cloud, and overall, my company has received a good deal on all the features that we have. We just have to understand how to explore it further.

Not directly because of Splunk, but the visualization that I have with the main aspects of scaling made us create custom dashboards that proactively detect the changes in scale, and then we can get ready for those changes. We don't have to spend time testing the new capacity when it's already being defined and envisioned by Splunk.

My advice to other organizations considering Splunk Observability Cloud is to watch out for your budget. If I could assess the impact of not having Splunk Observability Cloud, there would be a monetary impact with other solutions. For the business, we would lose resiliency of the system. To imagine the impact, it would be catastrophic.

Splunk has to think about how to redesign Observability Cloud. It came from SignalFx and AppDynamics to Splunk Cloud. It's a merge of different platforms into one, and this merge is being done at a pace where I expected more velocity.

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

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.

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.

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.

We primarily use Splunk Real User Monitoring to analyze performance bottlenecks and application transactions. It allows us to see how applications are experienced on the user side, making it easy to capture any bottlenecks or performance issues.

The most valuable features include user time tracking and the ability to analyze application load times. Splunk provides advanced notifications of roadblocks in the application, which helps us to improve and avoid impacts during high-volume days. It is very useful for identifying performance bottlenecks.

It would be beneficial to have more enhanced features with capabilities to adapt more integrated applications. Improvements in dashboard configuration, customization, and artificial intelligence functionalities are desired. There is room for improvement in customer support due to delays and standard feedback responses.

I have been working with Splunk Real User Monitoring for almost two years.

In terms of stability, I would rate it a nine out of ten. It is a very stable solution.

Splunk Real User Monitoring is definitely scalable. I would rate its scalability a nine out of ten.

Technical support is rated an eight. There is some delay in their in-depth responses and standard answers to questions.

Positive

I worked with Splunk alongside Dynatrace. Before Splunk, I did not use any other services.

It takes about an hour to set up the client for real-time monitoring.

We have a separate team for deployment, consisting of about three to four people.

We have achieved a return on investment between 10% to 20% as it helped in removing roadblocks, which could lead to more savings with wider usage.

Splunk is a little expensive, however, it is in line with the current market pricing. I would rate the pricing an eight on a scale of one to ten, as it reflects the going rate in the market.

I would recommend this product to other users because of its capabilities in monitoring and analytics. 

I rate the overall solution eight out of ten, considering the comparison with other products like Dynatrace.