Prometheus is a service monitoring and time series database, which is open source.
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Splunk Observability Cloud
Score 8.5 out of 10
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Splunk Observability Cloud aims to enable operational agility and better customer experience through real-time AI-driven streaming analytics allowing accurate alerts in seconds. It is designed to shorten MTTD and MTTR by providing real-time visibility into cloud infrastructure and services.
It is easier to setup, but learning curve is quite moderately steep. Prometheus is a best-in-class tool for engineers and SREs in cloud-native environments. When extended with tools like Thanos or Cortex, it can rival commercial platforms in scale and capability—but requires …
As I mentioned earlier, Prometheus had an added advantage that we were able to monitor CPU, RAM, Disk Space, process monitoring which other tools did not provide us Some tools were obsolete, and other were costly when we wanted this good feature , only Prometheus delivered on …
We considered TICK stack as an alternative to our Prometheus/Grafana setup that we have for capturing, storing and visualizing the time series data. But it seemed more complicated to learn and required a separate DB called InfluxDB to be setup. So, after all these considerations, …
The software is very lightweight and can be hosted with minimal resource usage. Many exporters exist for various software. Prometheus has a powerful and flexible query language (PromQL) that allows analyzing your data easy. I use this software with its various exporters, …
Highly customized pricing plans to choose from. Lower pricing for the same features compared to competitors. Easy to reach the support team, which provided detailed documentation and helped set up the Prometheus. Monitoring metrics gets very easy after the integration with …
Since Prometheus is free to use and provides all the features we required we went with Prometheus if any feature is missing then we can consider other paid solutions like data dog.
It was easy to implement in our enviroment compared to the other products which has a lot of challenges in the POC period it self. We have been looking for a quick solution as it was implemented during COVID, hence we were trying to take advantage of this software to see how it …
Prometheus was built to monitor CLOUD infrastructure. InfluxDB also has a good design to monitor time series but does not have a design for these demands. InfluxDB would need customization to integrate with Grafana and other third-party solutions. A disadvantage of InfluxDB is …
Both were present in the toolset. Splunk Enterprise was used in more of the log observability tool than the monitoring of the service. Prometheus was used mainly on the server and services monitoring and alerting capability used to have a stable production environment. …
Out of all the products that we did POC, Prometheus was the easiest to integrate the tool with our storage grid on which some of our most business-critical application workflows run. Prometheus was not only able to solve the monitoring problem but also provided a variety of …
The installation of Nagios core is quite difficult and the whole system seems us like a huge headache for us the entire team is not much happy with Nagios core so we take the decision and switch to Prometheus and were really happy with our decision and satisfied.
prometheus brings the power of real-time graphs to the land of open source ( reference included ). It's lightweight and doesn't seem overkill if you're a startup company and do not have a heavy traffic load. Great for starting out on small to mid-scale. as traffic rises, you …
The reason Prometheus stands tall against its competitions is because it is generic. Hence, it can be used to monitor all kinds of services, be it Database, Servers etc. Whereas CloudWatch only monitors over AWS services. Another reason is its huge availability of integrations …
Prometheus is great for quantifiable metrics. Loki is intended for log aggregation. Depending on project a different combination of data source types may be needed. However, quantifiable metrics are predominantly supported by Prometheus. Other data sources like elastic search …
Prometheus is better as a monitoring tool than graphite as graphite is a passive time series database with a query language. Prometheus has a rich data model by capturing metadata with labels which allows for easy filtering and querying. For a clustered solution, graphite maybe …
Prometheus is cheaper, and you can quickly set it up compared to others. It is integrated with most of the open-source monitoring and alerting tools and can help small companies in having a cost-effective solution early in their stage.
I tested out this solution and vetted out a few other solutions as well and ultimately ended up going with Prometheus due to a few specific reasons. Prometheus has a freemium option that allows a company to maintain cash flow while not sacrificing the quality of the product. It …
Prometheus is similar to some of its competitors but delivers with regards to metrics; being used internally by Google and other cloud-native companies like ours gives us the confidence that the alerting industry stakeholders view it as a long-term solution that the community …
We evaluated Datadog and New Relic but cost-wise, these 2 are very expensive. Prometheus does require more leg work to match the feature sets but other than time, the cost is free. Pairing with Grafana, Prometheus can pretty much match features with the big players and still …
If you combine Prometheus with Grafana, what you get is just amazing. it is basically the best ecosystem that I have seen. Grafana just makes those fancy "iron man" kind of dashboards and it just looks so appealing to your eyes. I have implemented NAGIOS core earlier for …
Datadog pushes intom proprietary ecosystem and pricing structure.Compared to self hosted prometheus and grafarna but it gave headache og managing our own monitoring infrastructure at scale.Prometheus is excellent for scraping cluster metrics but it doesnt handle distributed …
it could stack up against this version of Splunk because in this instance of having the cloud option as an available use case it furthermore has more use cases and the options for the data to always be readily available will furthermore allows for analysts to review the data in …
I guess scale is the main factor against grafana and ease of use against amazon elasticsearch service and also i have used signoz and ELK Stack also, but stability Splunk Observability Cloud gives is too good and also it comes with high avability and you have to maintain …
We initially chose Splunk Observability Cloud because it promised full-stack visibility and tighter integration. The other tools didn't offer this as part of the core package. Their analytics and real-time dashboards looked strong during the demo but it turned out to a lot …
I selected Splunk Observability Cloud because it focused so much on OTEL standards which will help us in future as OTEL is covering most of the observability standards. And also it has the best Kubernetes observability as I already explained it has several predefined dashboards …
Splunk Observability Cloud stood out for its real-time data ingestion, native OpenTelemetry support, and seamless correlation between metrics, traces, and logs, which gave us faster root cause analysis and better end-to-end visibility compared to Grafana setups that required …
To be honest, Datadog is very similar to Splunk and LogScale to a lesser degree, but it is just as good if you don't need too complex observability. Grafana is still growing and might reach the same level soon.
It's able to quickly detect and resolve issues across the entire spectrum of deployments including on-premises, public cloud, private cloud, hybrid cloud and multicloud
The above applications have their own use cases. Thousand Eyes or Sitescope is used for URL monitoring and Splunk is used for application monitoring. Appdynamics is also used for application monitoring and can monitor the server very well but it lacks when searching in logs …
Splunk is superior in many ways to these solutions when I'm comes to ingesting, storing, manipulating, and using data, but dynatraces automatic agents do make it much easier to use out of the box. Nagios seems much cheaper but does not provide as much functionality as Splunk. …
SQL is a great tool for smaller quick checks. When trying to monitor several different environments, applications, APIs, several thousand devices, connections, and technology, it just doesn't stand up to what you need. Splunk Infrastructure Monitoring has really stood out …
We are having other monitoring tools like AppDynamics, Dynatrace, Datadog and already using their end-user monitoring capability. Most of our customers are looking for agent-free monitoring where they don't want to instrument any agent on their client-side (as it might …
Splunk Infrastructure Monitoring provides far superior options for anybody using a complex hybrid multi-cloud environment and allows both your SOC and NOC to work together on the same data while driving their own insights.
We found other products are still in the old world view …
This program works from the roots of the problem and creates a professional matrix for each of its users. This will give them more skills and resources to carry out tasks and reduce the difficulties of operating each of the processes of my work, as well as being An ally for the manipulation and operability of all your master data; Prometheus is very easy to recommend since it is a program that fulfills its mission.
Good for below cases 1. There is a front end and need to correlate data with front end data 2. multiple microservices and need to check the health of each system 3. correlate data from various sources 4. Application performance is a key to be captured 5. application performance is a key metric.
The first one is its Kubernetes container monitoring.
I really like this features because as we know how much K8s is vast and to manually monitor each part of the Kubernetes it takes so much time but Splunk Observability Cloud makes it easier. And even once we integrate K8s with Splunk Observability Cloud it gives us some prebuilt dashboards which gives holistic view of our Cluster and its nodes, pods, etc.
The dashbaord feature of Splunk Observability Cloud, it gives us full flexibility to customize our dashboard with a wide range of predefined chart types.
Now it also supports OTEL, which is a plus point for observability. As now everyone is moving towards Otel and in current market there are only few tools who supports OTEL based integrations, Splunk Observability Cloud is one out of them.
Customer Service: since this is an open-source tool, customer service is not that great. Generally, you get all answers to your problems in online forums, but in case you got stuck, nobody will assist you in a channelised manner. You will have to find the way out on your own, and it may become frustrating at times.
More metrics for dashboards shall be added per the application being monitored. Standards metrics will work in most cases but may not in specific applications. Therefore, customised metrics shall be created for some of the industry-standard niche applications.
An indicator for errors on the navigations pane so that we don't have to go through each tab.
As we go more and more cloud maybe you guys can implement a pay-as-you-use strategy so that small companies using it not frequently can also afford it.
That's it can't think of any and it wont let me skip to next question. Thanks
Good: Stable system with low error rate Easy to use for simple use cases Bad: UI is not very clear for complex usage Mobile view (when logged in from phone) is bad No library for .net
It is usable and one can learn if few people in the team are already using it. It can be difficult to understand at the beginning because of non intuitive UI and syntax of the rules. So, I've gone for 7 points as there is some room for improvement in user interface and rules syntax.
Overall a great tool to have in your toolbox, It is very intuitive and our entire staff uses the tool. It is easy to use and cost is very reasonable. Splunk also has excellent support team and very easy to work with. Every time we had a challenge, support team was able to help us with the end result.
Highly customized pricing plans to choose from. Lower pricing for the same features compared to competitors. Easy to reach the support team, which provided detailed documentation and helped set up the Prometheus. Monitoring metrics gets very easy after the integration with Grafana. It also has a sophisticated alert setting mechanism to ensure we don't miss anything critical.
To be honest, Datadog is very similar to Splunk and LogScale to a lesser degree, but it is just as good if you don't need too complex observability. Grafana is still growing and might reach the same level soon.
The ROI mentioned during the purchase has not been achieved, however this could be due to lack of data from our side. 2 years of implementation is too early to calculate and confirm the ROI.