Building Cost-Effective Observability

As the digital landscape continues to evolve, organizations are increasingly turning to cloud-native technologies to modernize their applications and infrastructure.

Cloud-native technology offers a wide range of benefits, including enhanced agility, scalability and cost-efficiency; however, managing these complex and distributed environments can be challenging. This is where modern cloud-native observability comes into play.

Jump to:

• Global observability market 
• What is cloud-native computing, and what are its benefits?
• Cloud-native’s upsides come with challenges 
• How cloud-native observability can solve those challenges
• What do you look for in a SaaS cloud-native observability solution?
• Empowering developers’ effectiveness in the cloud-native age

Global observability market

Initially, companies that leveraged the global cloud migration movement created centralized business-critical systems; however, to fully realize the benefits of cloud computing, it wasn’t enough to simply “lift and shift” existing applications. Cloud-native patterns emerged, necessitating re-architecting existing systems, such as breaking up monoliths into microservices as well as shifting from managing virtual machines to orchestrating containers. These trends shaped today’s digital infrastructure, trading simplicity for complexity.

A recently published global Observability Tools and Platforms Market report from MarketsandMarkets projects significant growth in the sector, almost doubling its value of $2.4 billion in 2023 to $4.1 billion by 2028. It’s no surprise then that 71% of companies are concerned about the growth of their observability data and its associated cost, according to a recent observability report from Chronosphere.

Despite the increasing role of observability for companies, developers continue to express frustration with unreliable solutions. Chronosphere’s report also revealed that:

• 87% of engineers say using cloud-native architectures has increased the complexity of discovering and troubleshooting incidents.
• 59% of engineers say half of the incident alerts they receive from their current observability solution aren’t helpful or usable.
• 40% of engineers frequently get alerts from their observability solution without enough context to triage the incident.

But before we go into how these common pitfalls can be solved with modern observability technologies, let’s dive into cloud native and its benefits.

What is cloud-native computing, and what are its benefits?

Cloud native and DevOps have completely changed the way we write, deploy and run our environments. Here’s a brief overview of cloud-native computing and details about its benefits.

What is cloud-native computing?

According to the Cloud Native Computing Foundation, “Cloud native technologies empower organizations to build and run scalable applications in modern, dynamic environments such as public, private, and hybrid clouds. Containers, service meshes, microservices, immutable infrastructure, and declarative APIs exemplify this approach. These techniques enable loosely coupled systems that are resilient, manageable, and observable. Combined with robust automation, they allow engineers to make high-impact changes frequently and predictably with minimal toil.”

Prior to the advent of cloud-native technologies, software development and deployment followed a monolithic, centralized approach. Developers used to build large, sophisticated applications that were intrinsically linked to specific underlying hardware and IT infrastructure. Applications were written by developers but “thrown over the wall” to be deployed by operators. This dysfunction led to the DevOps movement, which increased transparency, communication and collaboration between these two groups.

With the rise of cloud-native computing, the way digital environments are built has been transformed. Leveraging new approaches, modern and dynamic digital environments have become decentralized, agile, scalable and cost-efficient.

The benefits of cloud-native computing

Designed to be modular and loosely coupled, cloud-native computing provides enhanced agility and faster development cycles, accelerating time-to-market. Under this framework, development teams can work on individual microservices independently without disrupting the entire application; also, the infrastructure automatically scales up and down as needed.

Cloud-native computing’s modularity and virtualization offers the opportunity for continuous integration and delivery, allowing for frequent and automated deployment of updates. Cloud-native applications are designed for scalability.

Cloud-native’s upsides come with challenges

While cloud native introduced a plethora of benefits, it also created challenges. From unprecedented data growth to the need to engineer reliability and adapt existing traditionally configured applications, there are key pain points roadblocking and constraining cloud-native developers today, which ultimately impacts a company’s performance, operating costs and ROI.

Data growth and cost management

The amount of data that cloud-native applications generate is massive. From logs to metrics and traces, developers must stay on top of all this data influx at all times or risk inadvertently causing massive bill overages.

Storage, processing and maintenance costs rapidly escalate, generating data debts. Organizations need to implement efficient data collection, storage and analysis strategies to optimize data utilization and minimize data debts.

Impact on productivity

You won’t be able to hire your way to a cloud-native fluent workforce — there’s a shortage of engineers with deep cloud expertise, so investing in upskilling the existing engineers must be a part of your digital transformation. With the rapid pace of innovation in cloud-native technologies, keeping up with the latest features and capabilities available is one challenge; a bigger, more existential one is the decreased ability of engineers to understand system behavior and the user experience within these new, more complex cloud-native systems.

Effectively operating and understanding cloud-native systems requires a paradigm shift from just monitoring to monitoring and observability. In a nutshell, monitoring can alert engineers that something is wrong, but observability enables them to investigate and answer “why.” To maintain or even increase developer productivity, organizations need to invest in developer training, provide comprehensive tooling and establish clear processes to support developers in building and maintaining cloud-native applications.

Chronosphere details five steps to improve DevOps productivity in a cloud-native world:

1. Get the right cloud-native tools for the way you want to work.
2. Analyze, refine and operate observability data at scale.
3. Provide standardized templates and best practices to DevOps teams.
4. Optimize for speed and performance.
5. Ensure tooling is usable by all levels of engineers, not just power users.

New architectures necessitate new observability tools

The monitoring and observability solutions built for traditional on-premises environments can no longer keep up with the speed, scale and complexity of cloud native, nor are they built for the way that modern DevOps teams operate. These tools often struggle to handle the volume and complexity of cloud-native data, leading to blind spots and reactive problem-solving approaches.

Unreliability and customer experience

While virtualization — a core component of cloud-native environments — in theory provides all the necessary tools to avoid downtime and serve modern customer demands, putting it into practice is still a challenge.

The distributed nature of cloud-native systems involves numerous moving parts managed by multiple distinct teams across disciplines, all of which need to operate in concert to deliver reliable customer experiences. By implementing robust monitoring as well as a plan for coordinating incident responses to identify and address issues promptly, developers can minimize downtime and ensure a seamless user experience.

Yet getting cloud native right is critical to business success. Companies are competing to gain and retain online-savvy customers who blame the brand when they experience glitches in their consumer experience. In a recent online reliability report, 94% of respondents said apps and websites are less reliable today than one year ago, and they are left feeling frustrated (71%), annoyed (65%) and even angry (26%).

How cloud-native observability can solve those challenges

To effectively observe and manage cloud-native applications, organizations need to adopt observability solutions that are designed to handle the scale, complexity and distributed nature of cloud environments. But with so many observability solutions in the market, here are key considerations leaders need to consider.

Data challenges and reliability are not only linked to the amount of data generated and how well-orchestrated microservices are — collecting, processing and analyzing data in real-time is vital for developers to have immediate insights into their environments’ behavior.

Even with the increased volume of observability data emitted from cloud-native systems today, it is worth looking at adding distributed tracing if your developers are currently only leaning on metrics and logs to get a sense of system health. Distributed tracing, as the name suggests, was created to solve understandability and visibility problems engineers face that are unique to distributed systems.

What do you look for in a SaaS cloud-native observability solution?

There are several key features and characteristics that all companies should be looking for, especially when getting started with cloud native.

A SaaS cloud-native observability solution should provide comprehensive visibility into the health and performance of cloud-native applications and infrastructure. It should also collect and analyze metrics, logs, traces and events from various sources, including infrastructure, applications and any third-party dependencies or integrations. Key features include real-time alerts and a developer-centric design to help identify and resolve performance issues quickly.

Modern observability tools should provide cost, need, context and utility data and insight, cutting through the noise while driving performance.

Your next SaaS cloud-native observability solution should be able to:

• Tame data growth and control costs.
• Enable consistent availability and reliability.
• Increase developer productivity and improve the developer experience.
• Deliver world-class customer success services.

Empowering developers’ effectiveness in the cloud-native age

Not investing in cloud-native observability can have a heavy toll on organizations, leading to increased operating costs as well as loss of revenue and customers, causing them to fall behind in competitive markets. Chronosphere’s cloud-native observability solution addresses these challenges by helping companies manage runaway observability costs, reduce downtime, address and fix problems before they impact customers and improve the developer experience.

Built on a unique Observability Data Optimization Cycle, Chronosphere provides a comprehensive approach to observability. It not only mitigates the challenges posed by traditional observability platforms; it also optimizes data management, improves cost predictability and delivers robust data management and optimization.

The Chronosphere Control Plane: Mastering observability optimization

At the core of Chronosphere’s modern approach to observability is the Control Plane. It’s designed to tackle the challenges posed by traditional observability platforms while offering a transformative solution for cloud-native environments.

The Chronosphere Control Plane provides four interconnected components: Operate, Analyze, Refine and Centralized Governance.

Operate focuses on efficiency. It provides platform-generated optimization opportunities and mechanisms such as the Query Accelerator and Scheduler to ensure fast and effective queries. This leads to quicker problem-solving as well as time savings, improving engineering productivity.

Analyze allows organizations to understand their observability data’s value and cost in real-time. With features including Traffic Analyzer and Usage Analyzer, teams can identify high cardinality metrics, understand data usage and determine the utility of each metric, helping them make more informed decisions about their observability practices.

The Refine aspect empowers teams to transform their data based on need, context and utility. They can implement dynamic shaping policies and adjust them on the fly to reduce noise, improve data usefulness and control costs.

Centralized Governance brings accountability and control into the hands of teams. By setting quotas and assigning ownership of their data to others, it helps contain cardinality, control long-term data growth and avoid budget overruns.

Chronosphere is designed to reduce observability data volumes, control costs and improve troubleshooting efficiency; in action, it also brings predictability and eliminates surprise overages. This is how each component not only effectively addresses the challenges teams have with traditional tools but also the unique value Chronosphere brings to technical decision- makers.