Continuous Intelligence: Sponsored by Sumo Logic
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.
The era of real-time, data-driven businesses has arrived—do you have all the information you need to react and respond?
For Alaska Airlines’ website one way to keep systems running is to break them using chaos engineering and observability.
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.
Continuous intelligence can help enterprise leaders deal with complexity in operations, security and business intelligence.
Continuous intelligence (CI) is a strategic capability that integrates key technology elements to deliver real-time guidance on operational problems.
Continuous intelligence holds promise in use cases in varied industry sectors and horizontally across the departments of many enterprises.
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.
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.
Nearly every company in every industry has unique challenges and drivers around how to use data effectively to drive their business.
Observability is needed to help identify where Log4j is used and minimize any potential impact it may have until the software component is updated.
Organizations see the value in unified observability, but there are still several barriers preventing a business from attaining the full value of its data.
Advice for developing a continuous intelligence strategy to support digital transformation, reliability, and security efforts.
Global hybrid cloud infrastructures make it all the much harder to protect data. Organizations are looking to AI-based approaches that give them insights to support data sovereignty.
Due to the complexity of modern apps, the industry is undergoing a shift away from separate network and application monitoring tools towards AIOps.
Data-driven businesses are having to slow down new data initiatives, due to manual governance and security operations required to hold sensitive data.
A shortage of developers can lead to more reuse of components, which often are not vetted or updated. That can introduce hidden vulnerabilities into applications that are hard to detect with traditional monitoring tools.
The addition of new features is moving SOAR from supporting security operations centers to broader operational use cases including ITOps to DevOps.
Businesses are more likely to purchase security solutions from vendors that prioritize innovation and sell leading-edge solutions.
Software developers today have their own supply chains, assembling code by patching together existing open-source components with their unique code. While this leads to increased productivity and innovation, it has also created significant security concerns.
Security solutions that use continuous intelligence can derive real-time insights into cloud-native app security threats.
A recent research study found the vast majority of Kubernetes API servers (380,000) to be open to the internet. That makes cloud security all the more challenging, requiring better monitoring, observability, and insights into the interdependencies within cloud-native applications.
The first publicly-known vulnerability attacking serverless computing platform AWS Lambda has been found.
Observability must encompass the different systems that comprise modern applications, rather than a single system like in the early days.
Observability can help identify where software with newly found vulnerabilities is used based on how it performs and interacts within a larger system.
Many top vulnerabilities are in software libraries that have been used for years. Observability offers a better way (vs. traditional security approaches) to find and protect against them.
RTInsights editor Joe McKendrick and Sumo Logic CTO and Co-Founder Christian Beedgen discuss the changing requirements for security in the age of digital transformation.
Cloud-native security tools could provide the type of support teams need to stay on top of security threats, respond faster, and monitor more efficiently.
The path to AIOps in many states and in federal agencies is often guided by an AI Center of Excellence that develops best practices and captures internal knowledge.
Cybersecurity must become as flexible as the architecture itself to help companies pivot quickly and respond even faster. Continuous intelligence can help.
Modern observability solutions provide visibility into the workings of complex edge applications and help staff make data-driven decisions when investigating latency issues.
RTInsights editor Joe McKendrick and Sumo Logic CTO and Co-Founder Christian Beedgen discuss the changing requirements for meeting the availability and reliability requirements of today’s demanding users and customers.
Continuous Intelligence platforms leveraging multiple data sources can surface performance issues immediately, whenever they emerge.
Grammarly uses continuous intelligence and real-time insights to improve security and feature delivery time.
If your organization spends more time scratching its collective head about data quality or operational issues than it does asking unique and interesting questions, then you’re not just wasting time, you’re actively eroding your company’s future.
The specialization of many data center job fields may be slowing down the response time in crisis, especially in cases with poor team communication.
RTInsights editor Joe McKendrick and Sumo Logic CTO and Co-Founder Christian Beedgen offer advice for developing a continuous intelligence strategy to support digital transformation efforts.
Modern observability is needed to help organizations find if and where they are using software with recently discovered vulnerabilities.
Tasks previously performed by the security staff, such as vulnerability scanning, log analysis, and ticket checking, can now be automatically executed by a CI-based platform.
SiEMs are increasingly playing a role in identifying precursors to DDoS attacks and in helping mitigate the root causes of those attacks.
Turning security threats into proactive protection for the long haul requires an engaged security operations center staff.
The rise in costly cyber attacks, especially those involving ransomware, is stressing the cyber insurance industry and leading companies to invest in more sophisticated security solutions.
The need for sophisticated security for companies of all sizes is growing as ransomware hackers are setting their sights down market this year.
Note all outages are the same. Given that most organizations do not have unlimited IT resources, the severity of an outage to the business must somehow be quantified.
Ransomware attacks on Linux-based multi-cloud environments are increasing in both volume and sophistication.
Joe McKendrick, RTInsights Industry Insights Editor, and David Linthicum, Managing Director and Chief Cloud Strategy Officer at Deloitte, discuss the increased need for continuous intelligence in today’s tech-ladened modern world.
Thanks to greater access to technology like AI and blockchain, organizations may be able to fight deep fake threats and reduce this risk in the coming years.
Cloud observability delivers data insights to keep a cloud application or service running and it offers a way to better understand entire cloud systems.
The move to cloud accelerated during the pandemic persists, introducing management challenges as the complexity of multi-cloud environments increases.
Enterprise cloud migrations and the continued increased use of cloud intros new performance monitoring and management demands.
RTInsights editors Joe McKendrick, Lisa Damast, and Salvatore Salamone discuss why continuous intelligence is needed to address today's evolving cyberattacks.
DevOps and SRE professionals love the idea of the “democratization” of observability via collectively-maintained projects like OpenMetrics and OpenTelemetry.
The position of modern SRE is relatively new. Training courses and certifications offer a way to attain the needed skills.
Can an industrial metaverse supplement the digital transformation manufacturers are already going through?
Helen Beal, industry analyst, and Bruno Kurtic, Founding VP of Strategy and Solutions at Sumo Logic, discuss the need to use robust analytics to gain insights, simplify operations, and cut through the complexities.
Cloud security and information management (SIEM) provides companies with options no matter where they are on the digital transformation scale.
As the gaming industry moves to cloud and incorporates more technologies in 2022, complexity will grow making it harder for those responsible for maintaining availability and resolving problems.
Edge, like many other complex applications and systems, needs more than traditional monitoring and performance management tools.
Businesses need a view into complex digital systems. One option being considered is a solution that provides greater observability based on continuous intelligence.
RTInsights editors Joe McKendrick, Lisa Damast, and Sal Salamone discuss why continuous intelligence is needed to address the complexity of modern applications and operations.
Monitoring and observability collect information and provide visibility into what’s happening. Observability, however, ensures a rapid, accurate response where manual methods may delay a fix.
The best way to protect organizations is to learn from last year’s cybersecurity problems and guard against the newest techniques hackers are expected to employ this year.
Many businesses are considering the use of observability based on continuous intelligence to help improve the availability and performance of their applications and services.
Observability helps digitally transformed organizations make data-driven decisions that reduce operational and security issues as quickly as possible.
For all their promise, today’s new data-driven technologies present organizational challenges to implementers.
Pairing monitoring and observability is beneficial because not all problems identified by monitoring tools require sophisticated investigation.
Observability can help identify where Log4j is used and minimize any potential impact it may have until the software component is updated.
The year 2022 will bring growing acceptance of OpenTelemetry for observability and a new focus on developers and customer experiences.
A cloud migration can benefit from an observability solution that includes multi-cloud monitoring and application observability, as well as high scalability.
In addition to Amazon’s announcements, Sumo Logic announced four new Sumo Logic AWS Quick Start integrations and expanded tracing visibility into AWS Lambda functions.
As companies seek ways to use artificial intelligence they will find AI is best applied to tasks that humans can’t do as well or don’t want to do at all.
Companies must address security weaknesses in their networked applications as well as non-IT-controlled ones, and CAASM may finally provide a solution.
Today’s complex application development and deployment environments based on cloud need SOAR (security orchestration, automation, and response) technologies to define incident analysis and response procedures.
Success with enterprise intelligence requires a mix of technology, educational and cultural inititiatives across the organization.
Observability aims to proactively provide full visibility into the source of known and unknown problems in any type of environment.
IT operations in the enterprise is among the areas where continuous intelligences can provide near-term benefits.
An Airbnb security expert outlines how automation, AI and machine learning can support a security strategy, and where humans play a role.
SIEM offers real-time analysis of security alerts and aggregates activity across an entire network, making it an obvious solution for government departments.
Automation via a continuous intelligence-based security solution is one of the most effective ways to nullify the negative effect of the skills gap, avoid burnout, and help address understaffing as positions go unfilled.
Study reveals most cloud mature digital companies are seriously considering the benefits of continuous intelligence (CI) and are enthusiastic about accelerating their rollouts at a high rate.
Gaming companies need continuous intelligence to address the same user experience, app performance, and security issues as enterprises.
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.
In this RTInsights Real-Time Talk podcast, RTInsights editor Joe McKendrick talks with Michelle Zhou, co-founder and CEO of Juji
As companies become more reliant on software to drive revenue, reliability will be the backbone needed to become a digital-first business.
A five-year timeframe for shifting to intelligent systems may be tighter than it first seems.
SOAR works because it effectively delegates responses to security threats based on the type of event and the necessary intervention level.
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.
Enterprises have new opportunities to use emerging technology concepts like continuous intelligence to improve their customer experiences.
As gaming companies struggle to balance security, user experience, and performance, continuous intelligence could be the path forward.
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.
The benefits from application modernization extend far beyond efficiency and security to ease of management and better uptime.
Businesses need a data-driven approach that derives real-time threat insights from streaming data to fight modern cyber attacks.
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 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.
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.
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?
With data security becoming ever-more challenging, continuous intelligence can offer hope to the enterprise.
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.
Running an effective security operations center (SOC) is at the heart of an enterprise’s strong cyber defense.
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.
Organizations that look at data as they do any other critical corporate asset or resource will be the most successful.
We are in the midst of an unprecedented convergence of events accelerating digital transformation.
Sumo Logic delivers the first and only cloud-native, Continuous Intelligence Platform™ enabling companies to thrive in the Intelligence Economy.
Monitoring tools can be complemented with new solutions that leverage self-healing and autonomous operations.
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.
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.
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.
Native integrations and built-in monitoring, diagnostics, troubleshooting, and security dashboards with the Sumo Logic Kubernetes App.
Reduce downtime and solve customer-impacting issues faster with an integrated observability platform for all of your application data.
Proven machine learning analytics provide deep compliance, security and operational visibility across your hybrid environments.
Whether or not you believe the hype, observability is all about how to ensure overall system health and deliver reliable customer experiences.
With the introduction of cloud computing, businesses quickly saw the value and opportunity to offload infrastructure investments and scale resources.
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.
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 has entered the Business Intelligence (BI) and analytics lexicon.
Ultimately, real-time data analytics projects are most successful when they feature partnerships between the technology and business sides.
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.