Continuous Intelligence: Sponsored by Sumo Logic

Sumo Logic Continuous Intelligence

Digital transformation requires continuous intelligence (CI). Today’s digital businesses are leveraging this new category of software which includes real-time analytics and insights from a single, cloud-native platform across multiple use cases to speed decision-making, and drive world-class customer experiences.

When Observability is Good for Chaos

For Alaska Airlines’ website one way to keep systems running is to break them using chaos engineering and observability.

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A Shift to Real-Time Business Equals to a Shift to Continuous Intelligence

Continuous intelligence delivers real-time analytics and insights into what’s happening and an understanding of the dynamic interactions that occur throughout a company’s digital infrastructure.

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How Continuous Intelligence Cuts Through Complexity

Continuous intelligence can help enterprise leaders deal with complexity in operations, security and business intelligence.

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Continuous Intelligence: Strategy, Technology, or Both?

Continuous intelligence (CI) is a strategic capability that integrates key technology elements to deliver real-time guidance on operational problems.

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CI Use Cases Across the Enterprise Organization

Continuous intelligence holds promise in use cases in varied industry sectors and horizontally across the departments of many enterprises.

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Why Continuous Intelligence? Why Now?

In this report you will learn about key industry trends — including accelerated cloud migration, the rising importance of rapid data insights, and the emergence of DevSecOps — and how they are converging to drive huge demand for continuous intelligence.

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Why Business Intelligence is a Big Deal

Business intelligence continues to evolve as developers incorporate the latest technology into their platforms, such as real-time analytics, natural language processing, AI, and machine learning.

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Gartner: AIOps, Observability Guide Post-Covid IT

Research firm Gartner shares its advice to IT leaders embarking on an AIOps strategy.

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Industry applications

Gaming COVID Boost Makes Continuous Intelligence Critical

Gaming companies need continuous intelligence to address the same user experience, app performance, and security issues as enterprises.

Continuous Intelligence

Sumo Logic Expands Continuous Intelligence Capabilities

Attendees to the Sumo Logic Illuminate user conference got an overview of new continuous intelligence offerings that are now part of the company’s platform.


Understanding Continuous Intelligence with Juji CEO Michelle Zhou

In this RTInsights Real-Time Talk podcast, RTInsights editor Joe McKendrick talks with Michelle Zhou, co-founder and CEO of Juji


Reliability is the Backbone of Digital Business

As companies become more reliant on software to drive revenue, reliability will be the backbone needed to become a digital-first business.

Best Practices

Enterprises Set Deadlines for Intelligent Systems

A five-year timeframe for shifting to intelligent systems may be tighter than it first seems.


7 Steps to Automate Cybersecurity Using SOAR

SOAR works because it effectively delegates responses to security threats based on the type of event and the necessary intervention level.

Continuous Intelligence

Continuous Intelligence Needed to Parry New Cyber Threats

Continuous intelligence can offer a unified view of many diverse security systems. And it helps to bring some level of simplicity to the complexity that continually grows in organizations today.


Add Intelligence to the Customer Experience

Enterprises have new opportunities to use emerging technology concepts like continuous intelligence to improve their customer experiences.

Industry Applicaitons

Why the Gaming Industry Needs Continuous Intelligence

As gaming companies struggle to balance security, user experience, and performance, continuous intelligence could be the path forward.

Continuous Intelligence

Cybersecurity Must SOAR to Address Today’s Threats

SOAR’s biggest strength is its ability to apply automation to security operations, freeing up analysts’ time from menial tasks to focus on more strategic initiatives.

App Moderization

Why Application Modernization Makes Sense

The benefits from application modernization extend far beyond efficiency and security to ease of management and better uptime.


Combating Savvy Cyber Attacks with a Data-Driven Response

Businesses need a data-driven approach that derives real-time threat insights from streaming data to fight modern cyber attacks.

Industry Application

The Need for Continuous Intelligence in Higher Ed

Because of the more open and dynamic nature of universities and colleges, the need for CI is even greater than that of some businesses.


Continuous Intelligence and the Automation Spectrum

Continuous intelligence used in decision support or decision automation has the potential to deliver significant benefits to organizations that need to react in the moment to dynamic situations.


Your Telemetry Data is Faster, Is Your Analysis?

Continuous intelligence (CI) platforms can be used to collect telemetry data from various sources, perform analysis on that data, make inferences about the data, and provide real-time insights that help businesses understand what’s going on.


Podcast: Understanding Continuous Intelligence

RTInsights editors Joe McKendrick, Jim Connolly, Lisa Damast, and Sal Salamone discuss continuous intelligence (CI). What is it? Why is it getting so much attention now?


How CI Tightens Enterprise Data Security

With data security becoming ever-more challenging, continuous intelligence can offer hope to the enterprise.

Continuous Intelligence

The Continuous Intelligence Report

Get the premiere industry report that quantitatively defines the state of the modern application stack and the shift in technology used by enterprises adopting Cloud and DevSecOps.

SOC Modernization

Solving the SOC Bottleneck: Automated Detection and Analytics

Running an effective security operations center (SOC) is at the heart of an enterprise’s strong cyber defense.


Day in the Life with Sumo Logic Cloud SIEM

Quick overview on Sumo Logic’s Cloud SIEM solution and how our scalable cloud-native platform helps SOC teams address multiple security use cases, including automatic detection and correlation for the threats that matter most.

App Modernization

Improve Data Lifecycle Efficiency with Automation

Organizations that look at data as they do any other critical corporate asset or resource will be the most successful.

Continuous Intelligence

Redefining Business Intelligence for Real-time Businesses

We are in the midst of an unprecedented convergence of events accelerating digital transformation.

Continuous Intelligence

Continuous Intelligence Platform Overview Demonstration

Sumo Logic delivers the first and only cloud-native, Continuous Intelligence Platform™ enabling companies to thrive in the Intelligence Economy.


Making the Most of Your Monitoring Tool Investment

Monitoring tools can be complemented with new solutions that leverage self-healing and autonomous operations.

Continuous Intelligence

Digital Transformation Requires Continuous Intelligence

Digital businesses are leveraging a new category of software, continuous intelligence (CI): real-time analytics and insights from a single, cloud-native platform across multiple use cases to speed decision-making, and drive world-class customer experiences.

SOC Modernization

Using Tech to Crack Down on Fraud in 2021

After a year of accelerated digital transformation and movement to the cloud, there are no more excuses not to be adopting cloud technology for your fraud detection strategies.

Use Cases

Digital businesses are leveraging a new category of software, continuous intelligence: real-time analytics and insights from a single, cloud-native platform across multiple use cases to speed decision-making, and drive world-class customer experiences.


Kubernetes Monitoring

Native integrations and built-in monitoring, diagnostics, troubleshooting, and security dashboards with the Sumo Logic Kubernetes App.


Faster Application Monitoring, Diagnostics, and Troubleshooting

Reduce downtime and solve customer-impacting issues faster with an integrated observability platform for all of your application data.

Cloud Security

Compliance and Security Solutions Brief

Proven machine learning analytics provide deep compliance, security and operational visibility across your hybrid environments.


The Origins of Observability

Whether or not you believe the hype, observability is all about how to ensure overall system health and deliver reliable customer experiences.


Cloud-native SIEM platforms

With the introduction of cloud computing, businesses quickly saw the value and opportunity to offload infrastructure investments and scale resources.

Additional Resources

Cloud Security

Cloud Security Monitoring & Analytics

Stay ahead of your changing attack surface by surfacing deep security insights. Built in the cloud for the cloud, Sumo Logic alleviates the challenges of security monitoring for your cloud and multi-cloud infrastructure.


Going Beyond the Three Pillars of Observability

This session will look at how to guide your observability strategy based on what you want to achieve, what your users care about, and the data you need to achieve it.

Continuous Intelligence

Continuous Intelligence Emerges as Successor to Real-time Analytics

Continuous intelligence has entered the Business Intelligence (BI) and analytics lexicon.

Business Intelligence

Real-Time Data Analytics Requires More Than Data Scientists

Ultimately, real-time data analytics projects are most successful when they feature partnerships between the technology and business sides.

Best Practices

Data Scientists are Swamped; What Do We Do About It?

Companies that want deeper, richer insights from their data scientists must leverage their teams’ expertise with strategic tools designed to automate tasks that create bottlenecks.

What is Continuous Intelligence?

As more businesses rely on software to operate and drive revenue, they’re becoming more reliant on real-time analytics to monitor, troubleshoot, secure their digital services, and implement digital transformation strategies. Continuous intelligence (CI) provides the needed real-time analytics and insights that enable companies to rapidly deliver reliable applications and digital services, protect against modern security threats, and optimize their business processes in real-time.

Challenges and drivers for CI

Every business operating today must transform into a digital business or risk being disrupted. The transition to digital operations generates an unprecedented volume of data from every touchpoint, customer interaction, and digital connection across the entire business and its ecosystem.

To put the data volumes into perspective, consider that data, in general, is expected to grow exponentially through 2025 to 175ZB. But from a continuous intelligence perspective, an estimated 30% of all data by 2025 will be machine data generated by digital transformation technologies and solutions. Percentage-wise that represents about a doubling of such data. 

All this data (much of it endlessly streaming) must be collected, indexed, analyzed, securely stored and safeguarded, and transformed into meaningful business value. Companies that can accomplish this will find that the data offers an incredible opportunity to know exactly what is happening inside a business the moment it happens. 

Such information is critical in today’s marketplace. Employees across organizations are always increasingly accountable for the overall health and security of their businesses. They can no longer credibly hide behind intelligence gaps caused by the plethora of function-based, outdated analytics tools that deliver siloed, piecemeal, and lagging insights. Organizations that cannot close these gaps in intelligence will get left behind and get lapped.

As companies rely on speed and agility for success, a business imperative is emerging to unlock the intelligence layer hidden inside their functions, teams, leaders, and employees so it can act as a unified source of faster innovation, higher creativity, real-time responsiveness and execution success. Access to this layer must be real-time, continuous, and supported by a single source of truth that brings siloed data together in a common, seamless, and always-on experience.

To close intelligence gaps, companies are unlocking their intelligence layer with continuous intelligence. Continuous intelligence can deliver real-time insights and enables organizations to accelerate their digital transformation and the ubiquitous shift to cloud computing and modern application architectures. 

Embracing an architectural transformation

Increasingly, cloud-native is the architecture of choice to build and deploy modern applications that transform businesses. The architecture provides the speed and flexibility needed to develop, deploy, continuously improve and secure  applications to stay competitive and meet user expectations, essential requirements for businesses operating new services in a digital world.  

The benefits of cloud-native applications realize the promise of truly distributed application  architectures with almost infinite scalability and elasticity than their inflexible, monolithic counterparts.. Cloud-native applications are a collection of small, independent, and loosely coupled services, making use of microservices and containers that use cloud-based platforms as the preferred deployment infrastructure. 

Microservices provide the loosely coupled application architecture, which enables deployment in highly distributed patterns. Additionally, microservices support a growing ecosystem of solutions that can complement or extend a cloud platform. 

Another aspect of a cloud-native deployment is the use of serverless computing. Serverless computing is a cloud-computing execution model in which the cloud provider runs the server and dynamically manages the allocation of machine resources. From a modern application perspective, serverless is an event-driven environment in which containers are loaded and executed based on some condition being triggered. For example, that condition might be an API call or the time of day.

Using an architectural approach that embraces these technologies delivers several benefits, including: 

Faster development and deployment: Time to market is a critical differentiator in today’s marketplace. Cloud-native applications using modern DevOps techniques allow businesses to automate many aspects of application development, testing, and deployment. As a result, businesses can quickly create new applications and rapidly deploy them. Thus, they can react to market changes and meet changing customer priorities.

Reduced costs: Cloud-native applications benefit from containerization. Why? Containers make it easy to manage and secure applications independently of the infrastructure that supports them. Increasingly, businesses are using Kubernetes to manage containers and resources in the cloud. When Kubernetes and containers are combined with enhanced cloud-native capabilities such as serverless deployment, businesses can run dynamic workloads and pay-per-use for compute time in milliseconds. This ultimate flexibility in pricing is enabled by cloud-native.

Flexibility to incorporate new technologies: Businesses need to keep pace with rapid changes in the field. That may require adding new analytics methods to enhance the capabilities of an application. For instance, a customer support service hub might want to incorporate different voice capabilities (e.g., speech to text features and vice versa using newly available natural language processing routines). A cloud-native architecture would use APIs to easily connect different (and new) analytics solutions offered as microservices. 

Flexibility also includes the ability to scale and burst "at will" to handle the unpredictable business cycles of on-demand services. There are numerous examples where such capabilities are needed including ramping up capacity and service for Black Friday, Cyber Monday, a sporting event like the Super Bowl, Presidential elections, or a natural disaster. Flexibility also is needed to adjust to major market disruptions such as those brought on with  the onslaught of Covid.

The critical role of continuous intelligence 

The many benefits of such an application architecture shift show why the cloud-native approach is popular and gaining more converts every day. However, cloud adoption introduces new issues that can render traditional management, monitoring, and troubleshooting solutions obsolete. Such solutions are either overwhelmed, present too many false alerts, or miss critical insights completely. 

As such, continuous intelligence solutions are needed. They typically offer several features, characteristics, and benefits attuned to the needs of modern business today. Specifically:

  • Modern application architectures break workloads down into small components and distribute them across cloud environments. This creates complexity, introducing more components, systems, and signals to manage, capture and analyze. Continuous innovation requires continuous intelligence to speed quality improvements and better manage these complex systems and services.
  • Multi-cloud adoption drives digital sprawl due to siloed architectures and management tools that provide only partial views, do not operate in real-time, and are not scalable for cloud environments. Multi-cloud agility requires continuous intelligence to enable a single pane of visibility across the entire heterogeneous architecture environment in real-time and across multiple use cases.
  • Security complexity arises as the surface area of attack expands across a perimeter-less digital footprint. Organizations often lack the skilled analysts and cloud-native tools needed to secure this new world. Today's increasingly sophisticated threats require continuous intelligence to automate and speed threat detection and response and to filter the real threats from the noise.
  • Collaboration becomes more important as teams struggle with antiquated, siloed systems that only present a partial view of data and lack real-time context around what is happening broadly across their organization. Continuous collaboration requires continuous intelligence to enable all functions to operate with contextual insights from a single source of truth – their modern application – to speed decision-making and eliminate time wasted debating which data from which tool source is relevant.
  • The overwhelming volume of data continues to grow unabated, and while companies must store and secure it, they are ill-equipped to extract value from it. Continuous data requires continuous intelligence to transform a burden into real-time value that can contribute to business success and competitive advantage, addressing various intelligence needs across innovation, operations, security, and customer experience use cases.

Who needs continuous intelligence? 

Many personas can use continuous intelligence within an organization for different purposes. Examples include: 

  • Developers can use continuous intelligence to build better software faster by gaining end-to-end observability across logs, metrics, and traces to find root causes.
  • Security staff and analysts can use continuous intelligence to automatically triage alerts, detect threats across all data sources, and speed up incident investigations.
  • IT operations staff and site reliability engineers can use continuous intelligence to maintain the high reliability of applications and infrastructure. 
  • Line of business leaders can use continuous intelligence to track their business service level indicators (SLIs), key performance indicators (KPIs) and key risk indicators (KRIs) in real-time to serve and optimize business operations across all parts of a digital enterprise.

CI also is a powerful tool for others. For example, cloud architects can use continuous intelligence to accelerate cloud adoption by gaining real-time monitoring of their migrated workloads in the cloud. And compliance officers and teams can use CI to quickly and easily demonstrate compliance readiness and maintain security best practices. CI application areas

Businesses using continuous intelligence can have insights into all operational areas. Some of the main uses of CI include:

  • Operational intelligence for DevOps observability: Continuous intelligence can help reduce downtime by finding, investigating, and resolving customer-impacting issues faster with real-time alerting and dashboards for all data, including logs, metrics, traces, meta data and telemetry.
  • Security intelligence: Continuous intelligence provides real-time analytics and security insights for apps and infrastructure. It can be used to support the entire spectrum of security use cases—from logging compliance data to monitoring and securing hybrid clouds to modernizing Security Operations Centers (SOCs) with automated threat detection, incident investigation and threat hunting.   
  • Business intelligence: Continuous intelligence can help companies make smarter business decisions faster by harnessing the data available throughout the organization to improve time to market for new features and offerings, better understand customer patterns and behaviors, and track business SLIs, KPIs and KRIs to understand real-time business performance of digital operations and services .

Why CI and why now?

CI is being more widely adopted across many industries and for many applications. The reason: the trifecta of mega trends of cloud computing, continuous innovation and microservice architectures, and proliferation of devices and endpoints from mobile computing and IoT is causing a perfect storm of data volume, velocity, variety, sources and tools. Businesses now have huge amounts of streaming data that are ripe for collection, indexing,  analysis and inclusion in business processes. And a new set of modern application and infrastructure technologies (cloud, container, orchestration, database, storage, custom code, services and security) ( to make use of that data are now emerging and gaining adoption traction. .

The combination of lots of streaming data and solutions to derive actionable intelligence from that data means CI can deliver significant benefits to businesses of all types and sizes. For example, a financial institution could use CI for real-time fraud prevention by detecting malicious transactions and stopping them before they are executed. An online retailer could use CI to provide an enhanced customer experience and improved service when a customer contacts a call center or moves through the product selection and purchasing process online. Or a utility could use CI to optimize resources and dynamically load shift and load balance in real-time as energy demands surge (or drop) throughout the day.

The bottom line is that continuous intelligence helps businesses make decisions while events are happening. It brings meaning to real-time data and helps organizations in a wide variety of industries.