Why Unified Observability is Critical for Multi-Cloud and Hybrid IT Success?

Misplaced data in a multi-cloud or hybrid IT setup can significantly increase your cloud costs, whether due to increased data egress fees, over-provisioned resources, or other latency-induced issues. Keeping track of this data can become challenging, especially since the total data volume generated and consumed globally has exceeded 149 zettabytes as of 2024.

This is where unified data observability comes in. With an observability solution/platform, you can gain a centralized view of all your data across multiple environments, enabling you to monitor, track, and optimize your data in real time. This unified approach not only helps you minimize costs but also ensures better decision-making, improved performance, and enhanced security. Let’s explore how implementing such a solution can bring clarity to your data operations and how we can help you build a tailored observability platform for your unique needs.

What is Unified Observability?

Unified data observability is a strategy for monitoring and managing system performance by consolidating key data, such as metrics, log data, and traces, into a single, centralized platform. In a hybrid IT environment with distributed storage across both on-premises systems and the cloud, this approach enables a secure, end-to-end view of your infrastructure. By providing comprehensive visibility, it simplifies the process of detecting issues, optimizing performance, and enhancing data-driven decision-making.

The Pillars of Observability

Observability depends on key aspects that work together for overall system health and reliability. These core elements, often referred to as the “Pillars of Observability,” guarantee real-time data engineering, effective application performance monitoring, and a birds-eye view of the entire system.

1. Freshness: The first pillar ensures that your data is always current and relevant by tracking its timeliness and accuracy. By allowing your operations team to monitor all states of a system (both internal and external), observability detects delays or stale pipelines, which is vital for time-sensitive decision-making.

2. Distribution: Understanding the distribution of your data, its range, mean, and standard deviation, is a critical aspect of true observability. With actionable insights into this distribution, you can quickly identify unusual patterns that may indicate potential issues in your systems.

3. Volume: The third pillar ensures your IT infrastructure is built to handle voluminous data migration throughout your ecosystem. This is crucial for those planning for or undergoing a digital transformation, as true observability will help them proceed as per anticipated data volumes.

4. Schema: The next pillar of observability pertains to the structure of your data, encompassing tables, fields, and data types. Observing this structure is crucial to ensure that updates are intentional and compatible with downstream processes, thereby safeguarding the system’s functionality across all internal states.

5. Lineage: Data lineage refers to the complete journey of raw data, covering all touchpoints between the data source and its final destination. This includes transformations that occur through ETL (Extract, Transform, Load) or ELT (Extract, Load, Transform) pipelines. By tracking this lineage, organizations can monitor data transformations, identify errors, and perform impact analysis.

Key Use Cases for Observability Solutions in Cloud Applications

Organizations are increasingly adopting unified observability solutions for cloud-based applications to gain better control and visibility over their systems. In fact, these solutions are known to drive measurable business value, offering a median annual ROI of 2x. Here is why:

1. Optimizing Cloud Performance and Cost Management

Many organizations rely on these tools and solutions to track real-time utilization of cloud resources. By gaining insights into this data, they can identify idle resources and over-provisioned instances and see how they affect overall cloud expenditures. In fact, observability solutions can reduce costs by up to 25%.

2. Reducing Mean Time to Detection (MTTD) and Resolution (MTTR)

The simultaneous analysis of all system data (logs, metrics, and traces) helps you detect issues faster. With unified observability solutions, your teams can correlate data points, such as unusual spikes in server load or network latency. This enables them to quickly pinpoint the actual cause and the location where it occurred, directly improving MTTD and MTTR.

In fact, as per Dimensional Research’s Observability Landscape Report, over 60% of organizations have reduced MTTR with custom-built observability solutions.

3. Monitoring Distributed Applications and Services

Performance in a distributed application, especially one built on a microservices architecture, relies on communication between multiple services spread across diverse environments. Unified observability tools are used to gain a comprehensive view of how these services interact, identifying bottlenecks such as latency in API calls or underperforming services that impact the application as a whole.

4. Strengthening Security and Compliance in Hybrid IT

You can also leverage observability tools to get centralized visibility into all activities across hybrid IT environments, including on-premises, cloud, and multi-cloud systems. These tools collect data, such as security logs, user access patterns, and system configurations, in real-time, allowing you to spot unauthorized access or other unusual activities.

For compliance, these tools/solutions can also help you identify system configurations that violate regulatory requirements like GDPR, HIPAA, or ISO standards. You can also schedule automated alerts to notify development teams of non-compliance, such as unencrypted data transfers or misconfigured access controls.

5. Ensuring Seamless User Experiences Across Platforms

Observability solutions are also used to ensure your app delivers a consistent user experience across all platforms. They monitor user interactions and track application performance across each platform, helping you identify any potential inconsistencies.

Why Unified Observability is Even More Critical for Multi-Cloud and Hybrid IT?

Obtaining a comprehensive view of your entire IT infrastructure can bring numerous benefits, particularly in distributed and hybrid IT environments. Let’s see how:

Centralized Visibility across Disparate Systems

In multi-cloud and hybrid IT environments, data is often stored across multiple platforms, resulting in data silos. Unified observability consolidates this data into a single view, equipping IT teams to monitor and manage everything from a single dashboard, without missing critical insights.

Faster Issue Detection and Root Cause Analysis

With a unified observability tool, your teams can quickly detect anomalies by correlating data from all environments. This end-to-end perspective enables faster identification of root causes, reducing downtime and ensuring smoother operations across complex infrastructures.

Improved Cloud Performance and Reliability

Observability solutions not only enable IT teams to monitor KPIs but also uncover gray areas that are often overlooked. These could include intermittent network delays, underutilized resources, or hidden dependencies between services that may degrade performance over time. Using AI-integrated analytics, they identify issues within this data and suggest performance improvements.

Reduced Tool Sprawl and Operational Costs

Multi-cloud setups often employ multiple monitoring tools, which can increase complexity and costs. However, with unified observability solutions, you can replace the fragmented tools with a single solution that streamlines operations and lowers overall expenses.

Proactive Incident Management

With automated alerts and notifications for unusual incidents, these solutions enable IT teams to prioritize the most critical issues first. Moreover, you can also use cloud observability tools to map dependencies between applications and infrastructure, predicting how one issue might cascade through the system.

Challenges of Implementing Unified Observability Solutions in Multi-Cloud and Hybrid IT Environments

While unified observability solutions offer immense benefits, implementing them across multi-cloud setups (a combination of AWS, GCP, or Azure) or hybrid IT environments (cloud + on-premises) is not very straightforward.

1. Siloed and Fragmented Data: More than 90% of business executives would agree that their data is siloed in a distributed system. Consequently, monitoring tools also operate in silos, leading to incomplete insights. This fragmented view does not give a complete picture of system health and performance.

2. Managing Separate Tools and Platforms: Working with siloed monitoring tools results in massive volumes of metrics and logs, which can overwhelm your teams. This diverse data also makes it hard to identify issues precisely. Moreover, you need additional resources and more time to handle such a setup, adding to the overhead.

3. Lack of Actionable Insights and Slow Troubleshooting: Without real-time insights into system performance, teams working in a hybrid IT environment struggle to connect events and metrics from different environments.

4. Security and Compliance Challenges: Multi-cloud setups often struggle to integrate and manage inconsistent security policies across platforms, each with its own security controls and monitoring tools. Moreover, they may have varying compliance requirements, such as GDPR for data in Europe and CCPA in the USA.

5. Operational Inefficiencies: Hybrid IT environments are inherently complex due to the demands of interoperability, performance, and security standards, as well as the numerous configurations required.

How to Implement Unified Observability?

Follow the steps below to implement this approach in your distributed IT environments.

Assess the State of your Existing Monitoring Process

Before you get started with a solution, it’s crucial to examine your current monitoring state. Start by evaluating the following:

1. Inventory of existing tools
2. Blind spots or process inefficiencies
3. State of your data—storage location, data formats, etc.

Use AI/ML for Smarter Insights

With the ability to process vast amounts of monitoring data, AI and ML technologies complement these solutions by automating tasks like pattern recognition, anomaly detection, and cross-platform data correlation. For instance, they can establish performance benchmarks and flag deviations in real time, helping IT teams identify potential issues faster.

Moreover, with predictive algorithms, AI/ML integrated tools can help you forecast performance issues and plan ahead of them.

Build a Strategy Aligned with your Business Goals

Implementing a data solution is not a one-off task. It is a complex and multi-step process that requires careful consideration and a well-planned strategy. Follow the steps below to devise an effective strategy that aligns with your long-term goals:

1. Identify what you aim to achieve, such as improved application uptime, enhanced cloud observability, or optimized costs.
2. Focus on tracking metrics critical to your business, like user response times or infrastructure utilization.
3. Fix performance benchmarks to track improvement over time.
4. Ensure that cross-functional teams, such as DevOps and IT, are aligned and trained on the solution.

Consider the Following for Platform Selection

Now that you have done the groundwork, move to platform/tool selection. Keep the following things in mind before deciding on a solution:

1. Platform’s Integration Capabilities: Ensure your chosen platform supports integration across all environments (on-premise, cloud, and hybrid IT).
2. Scalability Support: Opt for a solution that can scale with your growing IT infrastructure.
3. AI/ML Capabilities: Select data platforms that offer sophisticated AI-generated, actionable insights for proactive monitoring.
4. Cost and ROI: Evaluate the platform’s cost against potential savings and ROI. Prefer those with flexible engagement models.

Unlocking the Future of Cloud Operations with Advanced Observability Solutions

In today’s increasingly complex and distributed cloud and IT environments, traditional monitoring tools often struggle to keep pace. Especially with AI in the picture, a reactive approach, be it for anything, cannot suffice. Organizations must be proactive, even when it comes to monitoring their IT infrastructure and cloud environments, and this is where AI-powered observability solutions stand out. By analyzing data like logs, traces, and telemetry, these tools reveal hidden dependencies, predict performance issues, and prevent cascading failures.

Every organization, regardless of its size, should consider investing in such solutions. They’re essential for staying ahead of problems, improving resource utilization, and maintaining systems in a smooth-running state in dynamic environments. If you’re ready to improve your cloud operations but need help implementing the right observability solution, our cloud experts are here to guide you. Just reach out to us at info@technoscore.com.

Frequently Asked Questions: Understanding Unified Observability

What is Unified Observability?

It is an approach to monitoring and managing your whole IT environment, including cloud, hybrid, and on-premise systems, using a single platform.

Why is Unified Observability Important for Multi-Cloud Environments?

IT systems are hosted on several platforms in multi-cloud setups, each with its own tools, configurations, and data storage techniques. Uniform observability centralizes the entire monitoring process by eliminating blind spots and displaying data from multiple cloud environments on a single dashboard. This greatly simplifies the management and troubleshooting of complicated infrastructures.

How Does Unified Observability Reduce Mean Time to Resolution (MTTR)?

Data observability solutions provide a single source of truth, enabling teams to quickly and accurately identify and resolve issues. This makes it easier for your IT teams to identify and resolve issues more quickly, thereby improving system reliability and response times.

How Can Organizations Implement Unified Observability?

To implement a unified observability solution, start by evaluating the current state of your monitoring tools and identifying areas that lack proper visibility. Once you have an idea of your existing monitoring situation, find a reliable observability tool or platform. Find one that supports real-time monitoring, integrates with your existing systems, comes with AI/ML algorithms, and fits your budget. Training teams on how to transition to the chosen platform is also essential for effective implementation.

How Does Unified Observability Enhance Security and Compliance?

Unified observability tracks system activity, detects unusual system behavior, and provides real-time alerts for potential threats. It also helps ensure compliance by monitoring configurations against regulatory standards and generating audit-ready reports, making it easier to maintain secure and compliant systems.

What are the Benefits of Unified Observability for IT Teams?

Managing multiple systems and apps hosted on different platforms can overwhelm your IT teams, particularly if they have to juggle between separate tools for each. However, with a unified data observability tool/platform, they get centralized access and a holistic view of application performance across platforms. This reduces tool sprawl and workload, ultimately enhancing efficiency.