The 7-Point Checklist for Integrating Splunk Observability Cloud into Your AWS Environment

So, you have decided that it is time to say goodbye to outdated legacy monitoring systems. You are tired of relying on systems that only analyze samples of data. Ones that cannot keep up with the speed of your AWS environment (those containers do spin up and spin down quickly after all). It is time to embrace a new solution that can provide your team with the critical insights and support needed to promptly identify, triage, and resolve behavioral abnormalities – Splunk Observability Cloud.  

If your team has been contemplating an observational methodology, we encourage you to commit. The longer you wait to integrate a tool like Splunk Observability Cloud into your AWS environment, the more likely you are to miss the critical information needed to quickly identify and resolve issues, which could directly impact your team’s performance and your company’s bottom line.  

Positive performance can have a significant impact on your systems’ ability to convert end users into paying customers. A recent study found that decreasing page load time from eight (8) to two (2) seconds can increase conversion rates by as much as 74 percent. And on the other end of the spectrum, a critical application failure can cost between $500,000 and $1 million 

But before you start layering Splunk onto your AWS platform and recoding your software for observability, you need to get organized.

The 7-Point Splunk Observability Cloud Success Checklist  

At TekStream, we’ve had the privilege of assisting many organizations in implementing Splunk Observability CloudWe know what it takes for a successful implementation, and our team of experienced professionals has put together a list of the seven must-haves of any successful Splunk Observability Cloud integration into AWS and accompanying on-premise systems 

1. Name Your Implementation Destination 

Our number one piece of implementation advice? Start with the end in mind.  

Think ahead to the results and insights that will have the most significant impact on your team and organization. Ask yourself questions like:  

  • – What aspect of your business would benefit from observability? 
  • – What processes do you need to have visibility into? 
  • – What would the business benefit be if you had that information today? 
  • – What information do you need to be able to determine the health of those processes? 

Observability is very much a purpose-driven methodology, similar to the DevOps methodology. If there is a specific result you are trying to achieve through observability, then you need to integrate observability in a way that aligns with those goals.  

Identify your desired end-state, then work backwards to develop your implementation plan.  

2. Understand What Must Change to Prepare Your Organization for Observability 

Look at your current system and identify what changes you’ll need to make to become observability-ready.  You undoubtedly will have to make some changes to your code to support Splunk Observability Cloud. But code is not the only thing that may need to change.  

Existing processes, response protocols, and even team mindsets are all aspects of your organization that will need to evolve to embrace observability. Lay out a plan for how you will introduce observability and earn team buy-in before you think about implementing Splunk Observability Cloud.  

3. Determine Who in Your Organization Needs to Be Involved in The Implementation 

Yes, your developers will be involved. However, successful Splunk Observability Cloud implementation goes beyond any individual developer. Everyone involved in supporting the business process should be part of the transformation, including site reliability engineers (SREs), DevOps engineers, leadership, and more.  

Create a list of these individuals and match them to the specific implementation tasks needed for a successful integration. Be sure to include executive sponsorship and leadership support as well as who will be managing the project. Use this list to identify any gaps or overlaps in responsibilities.

4. IdentifAny Third-Party Systems That Need to Be Considered  

Your first-party systems are not the only technologies that may need to be updated. If your organization uses any third-party tool, you will want to ensure those systems also are integrated into your observability platform.  

Start with an audit of your third-party systems. Be sure to consider the limitations and supporting framework of each platform. Is it possible to integrate the current third-party system with Splunk Observability Cloud? Is it necessary?  

Once you complete your assessment, affirm that your timeframe and roadmap align with your findings. You may need to account for additional time, support, or resources.   

Additional Consideration: To accurately assess the ease of integration of your third-party tools, you may need to ask your vendors for additional access to the system. Check with each third-party platform to see if you have an opportunity to peek under the hood and gain insight into their system.  

5. Put Together a Clear Implementation Timeframe 

Do you have a specific end-time that your observability platform must be operational?  

Of course, nearly every organization will say, “as soon as possible.” However, we believe that a successful timeframe considers the scope of the implementation lift as well as the resources your organization can allocate.  

Align your timeframe directly to your roadmap by including sub-goals, milestones, deliverables, and other accountability metrics. Not only will this help you understand if your ideal timeline is too aggressive for the scope of the endeavor, but it also will help your team determine if additional resources are needed to complete the project within the desired timeframe.  

6. Clarify a Specific Approach to Your Implementation 

How are you planning on rolling out Splunk Observability Cloud? Are you only adding observability to new code? Are you rolling out one application or process at a time? Are you recoding all technologies before implementing them across your entire AWS environment?  

Some of these implementation options may be more practical and useful than others. Take the time to investigate the feasibility and bottom-line impact of each approach. Do not get distracted recoding systems that will not help your organization reach its performance monitoring goals.  

7. Choose an Implementation Partner

If the above sounds daunting, know that you do not have to go it alone. The right partner will guide your team through each of these points, lending their proven experience and process to better ensure a successful Splunk Observability Cloud implementation.  

At TekStream, we work with our clients to form a complete understanding of their observational goals, as well as the systems and processes that will need to be updated to achieve the desired outcome.  

From there, we will develop a timeline and implementation roadmap that takes you from where you are today to where you want to be with observability. Along the way, we will provide our strategic recommendations and insights across several project aspects that are imperative to a successful AWS integration

Get Started Today 

Ready to abandon your legacy monitoring tools in favor of a system that can keep up with the ephemeral nature of AWS? We can help. TekStream has proven experience assisting companies with their adoption of observability. Our team of dedicated experts stands ready to offer our support. Together, we will craft an implementation strategy that aligns directly with the needs of your team. Reach out to us today to get started. 

Interested in learning more about observability and how Splunk Observability Cloud can help you monitor and improve your AWS platform? Download our latest eBook:

Unlock Observability: 3 Ways Splunk Observability Cloud Works with AWS to Improve Your Monitoring Capabilities

According to the numbers, there are over 1,000,000 active AWS customers. In fact, there is a good chance that, like Netflix, Facebook, and LinkedIn, you, too, are using Amazon Web Services to support all or a portion of your cloud-based platforms and systems. Cloud technologies like AWS provide a host of benefits including scalability, cost-efficiencies, and reliability. But the very nature of cloud processing also introduces new layers of complexity. One critical added complexity is in monitoring cloud systems to identify and resolve issues. Traditional alert monitoring tools were not designed to address the ephemeral nature of cloud processing.  

Fortunately, Splunk has brought a full observability suite to market that integrates seamlessly with AWS’s portfolio of services to provide AWS users and their DevOps teams with the tools they need to improve the performance of their cloud-based systems. Below, we have laid out a brief primer on observability and paired that overview with three ways that the Splunk Observability Cloud works with AWS to streamline your monitoring.  

Introduction to the Splunk Observability Cloud 

While there is no shortage of observability tools on the market, Splunk’s acquisition of SignalFX in 2019, its subsequent additions to the platform, and its existing AWS integrations make it a powerful choice for organizations that use AWS as well as other leading cloud solutions like Microsoft Azure and Google Cloud Platform.  

Splunk offers a fully integrated observability set of products designed to bring all metric, trace, and log telemetry into a single source of data truth. Additionally, you can seamlessly merge this data with other Splunk Enterprise data such as security, IT and DevOps for the most comprehensive and integrated view of your environment. 

The Splunk Observability Cloud is comprised of several monitoring and observability products, including:   

  • – Splunk Infrastructure Monitoring: AI-driven infrastructure monitoring for hybrid or multi-cloud environments.  
  • – Splunk APM: NoSample™ full-fidelity application performance monitoring and AI-driven directed troubleshooting. 
  • – Splunk On-Call: Incident response and collaboration.   
  • – Splunk RUM (coming soon): Works with Splunk APM to provide end-to-end full-fidelity visibility by providing metrics about the actual user experience as seen from the browser. 
  • – Splunk Log Observer: Built specifically for SREs, DevOps engineers, and developers who need a logging experience that empowers their troubleshooting and debugging processes. 

Three Benefits of Integrating Splunk Observability Cloud with AWS 

For organizations already using AWS, Splunk works seamlessly with Amazon to provide DevOps teams with out-of-the-box visibility across their complete AWS environment.  With Splunk Observability Cloud, all data is shown within a single system, making it easy for your team to identify issues across any of the AWS tools you utilize.  

As data passes from your AWS services into your Splunk environment, it is analyzed in real time across the full Splunk Observability Cloud. The result is comprehensive reporting and monitoring that allows you to identify and respond to issues the moment they occur – regardless of your platform’s size. 

A Venn-diagram style graphic displaying the features of AWS and Splunk.

While there are several efficiencies and benefits to be gained by layering Splunk Observability Cloud onto your AWS environment, here are three that stick out to our team:  

1. Global Monitoring of Amazon Container Services 

Splunk’s Infrastructure Monitoring tool (part of the Observability Cloud) is built to specifically monitor the ephemeral and dynamic nature of container environments. Through this tool, customers can have key insight into Amazon ECS and Amazon EKS performance characteristics and containerized applications.  

Out-of-the box dashboards and reporting provide teams with the information they need to capture immediate value from the platform.  

2. Real-time Fidelity Tracing 

Are you tired of having to sample data or work with limiting data ingestion caps? Splunk Observability Cloud includes two powerful tools that, together with AWS, provide teams with end-to-end full-fidelity tracing. 

First, Splunk APM utilizes OpenTelemetry-enabled instrumentation to ingest all trace data. No more sampling. Splunk APM captures, analyzes and stores 100% of available trace data. Once captured, Splunk Real User Monitoring (RUM) can tie that trace data to specific user actions within your AWS environment.  

These systems work in tandem to provide your team with rich visibility into the bugs and bottlenecks that could harm your user experience.  

3. Automated Incident Response 

Not only does Splunk Observability Cloud provide real-time visibility across your complete cloud stack, but it also can reduce your team’s mean time to recovery (MTTR) through automated responses. Through the platform, DevOps teams can set automated remediations that fire regardless of human oversight.  

Built-in artificial intelligence and machine-learning capabilities help further improve the efficiency and latency of automated responses.  

Enhance Your AWS Platform with Splunk Observability Cloud 

If your legacy monitoring systems cannot keep up with the complexities and intricacies of AWS, it’s time to make a shift in your team’s mindset towards observability. By making the structural changes necessary to facilitate observability and embracing robust tools like Splunk Observability Cloud, your team will gain the capacity to improve the performance of your AWS environment.  

Interested in learning more about observability and how Splunk Observability Cloud can help you monitor and improve your AWS platform? Download our latest eBook: