Cisco Cloud Observability Operators

My main use case for Splunk Observability Cloud is infrastructure monitoring in the cloud.

An example of how I use Splunk Observability Cloud for infrastructure monitoring is mainly infrastructure alerts, in particular virtual machines, when there is a degradation in the system or an alert or event. Splunk Observability Cloud actually surfaces those.

The best features Splunk Observability Cloud offers include the ability to see all the various hosts, not only private cloud but also cloud services as well.

Having visibility across both private cloud and cloud services with Splunk Observability Cloud has benefited my work significantly, especially when trying to tell the story around particular incidents or issues and when they happen. In particular, anytime there is an adverse event that impacts the company, whether it is an infrastructure issue or a cloud issue, being able to get to root cause as quickly as possible has been extremely helpful.

Splunk Observability Cloud has positively impacted my organization by allowing us to have visibility into the environment. Historically, that has not always been the case. Once we implemented Splunk Observability Cloud, it definitely allowed us to get to meantime to identify and meantime to detect as quickly as possible.

Splunk Observability Cloud has helped improve my operational performance and my company's resilience. The biggest improvement is really improving uptime and reliability of the systems, getting to root cause as quickly as possible, minimizing impact as it relates to outages, and then being able to recover from those as quickly as possible.

I think the biggest improvement in Splunk Observability Cloud that Splunk is currently working on is just unification across all their products, not just Splunk Observability Cloud, but a single pane of glass to allow the engineers and operators to stay in one location.

I have been using Splunk Observability Cloud for approximately four years.

Splunk Observability Cloud is stable.

Splunk Observability Cloud has been able to meet all my use cases, so from a scale standpoint, I have not encountered any problems or issues.

Customer support has been great with Splunk Observability Cloud. The Splunk system team has always been there whenever there is an issue or problem. They have actually been very helpful in resolving those issues.

I would rate the customer support for Splunk Observability Cloud a 10.

I did previously use a different solution, which I believe was a custom-made solution built in-house. The reason for switching was mainly due to cost, and not only cost, but additional resources we had to add in order to customize that solution.

I cannot say whether I had a return on investment. The return on investment is probably mostly tied to operational efficiencies that I discussed before. I cannot say I have seen a reduction in employees needed. I do have to have added additional resources to actually help support observability and Splunk Observability Cloud, but most of my efficiencies have come in being able to identify and detect issues when they happen.

I do not get involved with pricing; my procurement organization deals with that. As it relates to setup, procurement actually gets involved and negotiates that. So I am not as intricately involved with that as my procurement colleagues.

I cannot say whether I had a return on investment. The return on investment is probably mostly tied to operational efficiencies that I discussed before. I cannot say I have seen a reduction in employees needed. I do have to have added additional resources to actually help support observability and Splunk Observability Cloud, but most of my efficiencies have come in being able to identify and detect issues when they happen.

I did evaluate other options along with Splunk Observability Cloud, with ScienceLogic being one of those. ScienceLogic and Splunk Observability Cloud were the two that were evaluated.

My advice to others looking into using Splunk Observability Cloud is to clearly define your use cases and your intent, and then gradually work towards those. I would recommend not trying to take on too much at one time. Instead, take on small use cases at a time and then build on those. Then probably the last thing is to continue to go back and check to make sure Splunk Observability Cloud is actually meeting its intent and its need and actually capturing the right signals for your organization. I would rate this product a 10.

I have been using Splunk Observability Cloud for five years now.

My main use case for Splunk Observability Cloud includes infrastructure monitoring, synthetics, APM, and RUM. For infrastructure monitoring, Splunk Observability Cloud serves as my primary tool for monitoring all the hosts or VMs that my technical organization provides for the rest of the company.

Regarding synthetics or RUM, they are used on a case-by-case basis because I do not want to turn them on for everybody. That is not part of my standard offering, where any applications that are internet facing that require more traceability and more digital experience are when those parts are used. IAM is my primary module that caters to almost 15,000 plus servers in the company.

The best features that Splunk Observability Cloud offers are the ease of configuration and the UI, along with the navigation which is simple to grasp for a non-Splunk user.

What makes the UI and navigation easy to use in Splunk Observability Cloud is the simplicity and the layout of the modules.

Splunk Observability Cloud positively impacts my organization as it is my primary infrastructure monitoring tool, and I believe it helps avoid outages related to OS and systems. It saves hours and hours of potential downtime or efficiencies using that platform.

Since using Splunk Observability Cloud and the Ansible Automation Platform, the overall mean time for resolve has reduced by 30x, averaging from 120 minutes down to 6.2 minutes, and I have potentially avoided 12,000 hours of downtime.

I believe that the ability to implement RBAC eventually will be a good thing for Splunk Observability Cloud. I know the product is slowly evolving in that area, but the sooner the better.

To improve Splunk Observability Cloud, I think seamless integration into Splunk Cloud, ensuring that there is a single UI for customers to use both products, is what will be a winner.

I think being able to deploy and manage the OpenTelemetry agents at scale is important for Splunk Observability Cloud. Upgrading or fixing and restarting that agent takes a lot of time and effort, so being able to make that experience seamless would help.

I chose eight out of ten because I think there are still improvements needed, such as fleet management and unified navigation. Once those are in place, I think it would definitely be a solid ten.

I find Splunk Observability Cloud stable so far.

Splunk Observability Cloud's scalability is pretty flexible and good.

Splunk Observability Cloud's customer support could be better as I think response times are pretty slow compared to the Splunk Cloud product. I would rate Splunk Observability Cloud's customer support a three out of ten.

I previously used an old tool called OSS that was rudimentary and utilized old industry standards, so I changed to Splunk for more modern industry standards.

Regarding my experience with pricing, setup cost, and licensing for Splunk Observability Cloud, I think pricing could be a little more flexible in terms of being able to draw from a pool license or being charged for what I consume versus buying a fixed count ahead and having to revise the licensing over and over year-on-year.

Before choosing Splunk Observability Cloud, I evaluated other options including Sumo Logic, ScienceLogic, LogicMon, and a couple of others.

I have not used Splunk Observability Cloud's AI capabilities enough to comment on its governance and security.

I have not used that product related to its AI capabilities, so I do not have any thoughts or experiences regarding accuracy and reliability of output.

I use AWS as my cloud provider.

I did not purchase Splunk Observability Cloud through the AWS Marketplace.

Splunk Observability Cloud has helped improve my operational performance and my company's resilience. Since it is my primary infrastructure monitoring tool, it is how operations get notified about potential degradations to the servers they cater to.

It is important for my organization that Splunk Observability Cloud has end-to-end visibility into my cloud-native environments, though I am more focused on-premise versus cloud-native. Cloud-native is still important, but my focus is primarily on-premise.

I assess Splunk Observability Cloud for helping my organization scale as effective because it determines what growth I would expect in terms of OS and server counts year on year. Being able to have a flex license pool model which does not restrict me to a certain number of hosts would be helpful.

I am not sure how I could calculate if Splunk Observability Cloud has helped reduce my mean time to detect (MTTD), so I do not know.

My impression of Splunk Observability Cloud's out-of-the-box dashboards and detectors is that they are good and easy to set up with less learning curve to get those up and running.

I assess this solution with an overall rating of eight out of ten.

Splunk Observability Cloud is primarily used for expanding APM and IM monitoring, correlating metrics, traces, and logs for better insights, and reducing MTTRs and MTTDs. In the SRE space, especially for digital mobile technology, it is set up to gather metrics and traces from applications. The RUM component is used to understand customer behavior, with traces and metrics ingested via the Splunk OTEL collector and RUM embedded through the Splunk RUM SDK. Dashboards have been built on this data to enhance correlation.

The main use case is seeing the correlation of metrics, logs, and traces in a single pane of glass, which we have successfully achieved.

The best features of Splunk Observability Cloud include the APM service map and real-time RUM monitoring, which track customer experiences. The service map helps understand the journey and identify pain points in services during issues. Correlating real user monitoring through RUM has significantly enhanced our understanding of customer pain points, allowing visualization of issues under APM.

Splunk Observability Cloud positively impacts our organization by enabling us to build dashboards around customer experiences and API backend layers. Previously, there were many hops with open-source tools like Grafana and Prometheus. Now, with metrics and traces consolidated, we gain a single view for correlation, significantly reducing MTTD, enabling detection of issues in under five minutes.

From an admin perspective, there are pain points such as difficulty exporting data into Excel and a cumbersome setup process. Improving the setup for data uploads via Excel and providing an option to download RUM data for analysis would be valuable improvements.

I have been using Splunk Observability Cloud for the last eight months.

Splunk Observability Cloud is stable.

We are expanding from one to ten applications next year. While there are no performance issues in viewing dashboards or when detectors fire, challenges remain with repetitive, manual setup processes. There is no templatization for quick growth, a feature we would love to see.

Customer support for Splunk Observability Cloud is adequate; it meets our needs but is not exceptional.

We previously used a combination of Grafana and Prometheus along with Splunk Enterprise. The limitations of these tools, coupled with the introduction of database monitoring and native Splunk OTEL capabilities in Splunk Observability Cloud, drove our transition.

There is a return on investment in terms of time saved. Traditional debugging required multiple interfaces and hours of effort, while now, with Splunk Observability Cloud, MTTD has decreased significantly, reducing investigation times from several hours to a maximum of thirty minutes.

My experience with Splunk Observability Cloud's pricing, setup cost, and licensing is positive.

We evaluated options including DataDog, Dynatrace, and Grafana plus Prometheus. DataDog is advantageous but expensive, making Splunk Observability Cloud the right fit for our budget.

My advice for those considering Splunk Observability Cloud is to ensure readiness in terms of data and integrations; simply using it for APM will not yield significant benefits. It is important to have a well-prepared OTEL strategy and to use RUM for its exceptional correlation capabilities.

Splunk Observability Cloud will help our organization scale over time, particularly with features related to database monitoring. SRE adoption and technical teams, such as DBAs, will benefit from more depth in database monitoring. Expanded adoption of Splunk Observability Cloud is due to its significant advantages.

It is very important for our organization that Splunk Observability Cloud offers end-to-end visibility into our cloud-native environments. Comprehensive visibility through improved adoption can significantly enhance operations.

We encountered significant challenges implementing Splunk AI assistant in the bank due to governance and security procedures. The absence of a BYOK model raises concerns about data exposure outside the environment.

We have not yet used Splunk AI capabilities in a production environment, so from our test environment perspective, we cannot assess accuracy until we implement AI capabilities in production. I would rate this review an eight out of ten.

As part of the monitoring team called ESOC, Enterprise Security Ops, we use Splunk Observability Cloud to have a bird's eye view on all the applications and infrastructure, observing how they connect with each other and how workflows among them occur. When we detect incidents, we deep dive into Splunk Observability Cloud to see the flow of the signals and identify possible connection issues with other systems they're connected to. We have been using Splunk Observability Cloud extensively these days.

At Progressive Insurance, we have a huge claims presence where the applications related to claims are high priority. Recently, we encountered an issue with claims documentation, which resulted in disruptions that affected applications using documentation, especially claims documentation, causing them to struggle. During this time, Splunk Observability Cloud was incredibly helpful as we drilled down into root cause analysis to assist those application teams in identifying what could have gone wrong—whether it was API calls, network issues, or pods being down. It took some time, but Splunk Observability Cloud really facilitated our investigation.

Seeing the whole signal flow aspect was really beneficial. We could visualize how the signals moved from one module to another, even with inferred systems, and that visibility assisted us in our analysis significantly.

One great feature of Splunk Observability Cloud is how it transitions from monitoring to observability. While monitoring involves looking at potential issues and health checks, observability allows us to view the system more from a signal flow perspective, and the visuals are much better. I can see the system clearly represented in front of me, allowing for better visualization and flow assessment. I hope to benefit even more from this at the conference.

An example would be how we analyze the interconnections between applications and pods, monitoring pod health and determining whether a pod is in a crash loop or just down, or if an application has an excessive number of pods down, which helps us present data more effectively.

I am continuously exploring more about it. Although I have been working with it for around two years, I am eager to learn more, especially with the incorporation of AI, which excites me about using Splunk Observability Cloud further.

I believe increased adoption is essential. While usage is steady now, the more application teams embrace it and avoid working in silos, the easier it will be to create a more cohesive structure.

We are relatively new to this, and I aim to explore further, especially during classes and sessions at the conference. I am thrilled about how AI is being incorporated to enhance dashboard functionality and visibility. Once we become more seasoned, we will grasp more about the necessary improvements.

Regarding the AI capabilities of Splunk Observability Cloud, I think its governance and security need much exploration. I am uncertain about what governance teams are doing within my company, but there are growing conversations about backdoor channels and misuse, emphasizing the necessity for strict guardrails and governance as key factors for adoption.

I have been using Splunk Observability Cloud for two years.

Splunk Observability Cloud is stable.

So far, its scalability at the user level has been good, but I am uncertain about the configuration or administrative level.

Customer support has been really good.

On a scale of one to ten, I would rate customer support an eight.

Previously, we used AppDynamics and Splunk Enterprise. We have not fully switched yet, but we are growing toward observability.

Time saved is definitely a factor. While I do not decide on monetary matters within the company, I can confirm that there has definitely been a time-saving aspect.

I advise others looking into using Splunk Observability Cloud to practice more, explore extensively, and aim to customize as much as possible according to their needs. I would rate this review a seven out of ten.

My main use case for Splunk Observability Cloud is logging. For logging, I monitor applications across a Kubernetes cluster and Docker containers.

The best features Splunk Observability Cloud offers include the API access. API access has helped me in my day-to-day work by allowing easy integration. Splunk Observability Cloud has positively impacted my organization because we have become huge clients.

Splunk Observability Cloud has helped improve my operational performance and my company's resilience. For example, it has helped with security and video. Splunk Observability Cloud helped with security by providing visibility into tiling.

I think Splunk Observability Cloud could be improved by being cheaper.

I have been using Splunk Observability Cloud for less than a year.

Splunk Observability Cloud is stable.

Splunk Observability Cloud's scalability is great.

The customer support is good. On a scale of one to ten, I would rate the customer support as a ten.

As far as I know, the organization has always used Splunk Observability Cloud, so I cannot say if we previously used a different solution.

I did not purchase Splunk Observability Cloud through the AWS Marketplace.

I do not have visibility into what changed after we started using Splunk Observability Cloud. I did not purchase Splunk Observability Cloud through the AWS Marketplace.

I have seen a return on investment, but that is outside my scope.

I am not the right person to share my experience with pricing, setup cost, and licensing.

I am unaware if my organization evaluated other options before choosing Splunk Observability Cloud.

Regarding Splunk Observability Cloud's AI capabilities, I think its governance and security are excellent. Regarding Splunk Observability Cloud's AI capabilities, the accuracy and reliability of its output depend on how long it takes; the longer it takes, the better it is.

It is not important for my organization that Splunk Observability Cloud has end-to-end visibility into our cloud-native environments. Overall, I assess Splunk Observability Cloud as great; it is overall very good for helping my organization scale. I cannot answer if I have seen time to value with Splunk Observability Cloud. I think Splunk Observability Cloud could be improved by being cheaper.

I would rate this review as a five overall.