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Business Wire
24-06-2025
- Business
- Business Wire
Komodor Redefines Kubernetes Cost Optimization with Holistic Automation Based on Performance, Risk and Right-Sizing
TEL AVIV, Israel & SAN FRANCISCO--(BUSINESS WIRE)-- Komodor, the platform for automating Kubernetes operations, health, performance, and cost management, today announced it has added advanced new cost optimization capabilities to its Kubernetes management platform. These new features enable organizations to intelligently reduce cloud spend while maintaining performance and reliability across their entire Kubernetes estate. Cloud didn't make hardware free—it made it a metered cost. Komodor understands that Kubernetes management isn't just about scale anymore, it's about cost-aware control. Most teams are overspending on compute—yet manually right-sizing workloads is nearly impossible due to a lack of expertise, the large volume of factors to consider, and the potential risks of making changes. Meanwhile, traditional cost optimization tools overlook business impacts on application performance, developer velocity, and platform reliability. Komodor takes a platform-centric approach, enabling engineering teams to analyze and visualize Kubernetes resources, application runtime data, logs, changes, along with 3rd party integrations to automate smarter risk-aware decisions for cost optimization. 'Cloud didn't make hardware free—it made it a metered cost. Komodor understands that Kubernetes management isn't just about scale anymore, it's about cost-aware control,' Dan Twing, President & COO, Enterprise Management Associates. 'Their intelligent automation helps teams optimize spend without compromising performance, which is exactly what's needed in today's complex, cloud-native environments.' Containing Cost not Performance As Kubernetes workloads grow in size and complexity, so does cloud spend. Engineering teams often over-provision infrastructure 'just in case,' resulting in idle resource waste. Meanwhile, mission-critical workloads can't be evicted, limiting autoscaler efficiency. But optimizing for cost alone often leads to misconfigured workloads, scaling failures, or reduced application reliability. Without a unified view of cost across clusters, namespaces, and environments, teams struggle to understand where savings can be safely achieved. Meanwhile, open source autoscalers like Karpenter and Cluster Autoscaler are helpful, but limited—since they don't account for workload diversity, service criticality, or real-time performance metrics. The Komodor platform's latest enhancements extend and augment native autoscaling with intelligent pod placement for bin-packing optimization, as well as real-time workload right-sizing, delivering up to 40-60% in additional savings. All without compromising stability or speed. 'In large scale Kubernetes environments, cutting costs without visibility into application behavior is a recipe for downtime,' said Itiel Shwartz, Co-Founder & CTO of Komodor. 'What organizations need is a way to optimize cost and performance—across the full scope of infrastructure and application operations. That's what we've built.' New Cost Optimization Capabilities The new capabilities available in the Komodor platform help teams transition from static resource planning to dynamic, real-time cost optimization—empowering them to eliminate resource inefficiencies without increasing risk. These include: Real-Time Spend & Allocation Visibility Unified cost views across cloud, hybrid, and on-prem environments with drill-down filters for clusters, services, and namespaces—for improved team accountability and smarter decision-making. Intelligent Workload Right-Sizing AI-driven resource recommendations based on real-world usage across CPU, memory, throttling, and scheduling signals—help prevent both overprovisioning and underperformance. Advanced Bin-Packing & Pod Placement Komodor actively resolves placement blockers (e.g., Pod Disruption Budgets, affinity rules, etc.) and extends autoscaler functionality to improve node utilization, reduce fragmentation, and accelerate scaling. Autopilot Mode with Guardrails Continuous unattended and customizable optimization profiles (Conservative, Moderate, Aggressive) and safety thresholds, ensure changes are always safe, traceable, and aligned with business priorities. Smart Headroom Management Intelligently reserves and manages extra compute resources (CPU and memory) across nodes to reduce provisioning delays and improve responsiveness during spikes, deployments, or rollouts—without overprovisioning. Availability The Komodor platform with advanced cost optimization capabilities is available immediately from Komodor and its global partner network. To schedule a demo or learn more about how Komodor can help your organization achieve performance-aligned cost savings, visit About Komodor Komodor reduces the cost and complexity of managing large-scale Kubernetes environments by automating day-to-day operations, as well as health and cost optimization. The Komodor Platform proactively identifies risks that can impact application availability, reliability and performance, while providing AI-assisted root-cause analysis, troubleshooting and automated remediation playbooks. Fortune 500 companies in a wide range of industries including financial services, retail and more, rely on Komodor to empower developers, reduce TicketOps, and harness the full power of Kubernetes to accelerate their business. The company has received $67M in funding from Accel, Felicis, NFX Capital, OldSlip Group, Pitango First, Tiger Global, and Vine Ventures. For more information visit join the Komodor Kommunity, and follow us on LinkedIn and X.
Yahoo
24-06-2025
- Business
- Yahoo
New EMA Research Uncovers How Early Adopters Are Preparing Enterprise Networks for AI Success
Based on a survey of 269 North American IT professionals involved in preparing their organizations' networks for AI applications, this new research serves as a practical guide for IT decision-makers embarking on their AI initiatives LAFAYETTE, Colo., June 24, 2025 /PRNewswire/ -- Enterprise Management Associates (EMA™), a leading IT research and consulting firm, today announced the release of its latest research report, "Readying Enterprise Networks for Artificial Intelligence," authored by Shamus McGillicuddy, vice president of research for network infrastructure and operations at EMA. As artificial intelligence (AI) adoption gains momentum, network readiness is emerging as a critical success factor. AI workloads generate unpredictable bursts of traffic, demanding high-speed connectivity that is low latency and lossless. AI adoption will require upgrades and optimizations in data center networks and wide-area networks (WANs). This is prompting enterprise IT teams to rethink, re-architect, and upgrade their data center and WANs to support AI-driven operations. EMA's new report serves as a strategic guide for IT decision-makers who have started their AI journey and: Examines how enterprises are preparing their networks for AI Explores changes to data center networks and WANs Investigates some of the security implications of these network Identifies changes made to network observability tools Explores some of the basic aspects of overall AI strategy, such as who leads these projects and what kinds of technologies companies are adopting "Networks will make or break enterprise investments in AI technology. IT organizations are well-aware of this fact. However, preparing networks for AI will be expensive and complex," McGillicuddy said. "This research shows that AI workloads will be distributed across public clouds, data centers, and the enterprise edge. This kind of architecture requires improvements to both data center and wide-area networks." Some of the key findings from the report include: The top business challenges to networking for AI are security risk (39%), budget issues (34%), and difficulties with keeping up the pace of AI innovation (33%) 42% of companies have established AI centers of excellence to lead strategy across technical teams and business units Organizations that can automatically apply quality of service or routing policies specific to AI-related traffic report more success with preparing their networks for AI This independent research is sponsored by Aryaka, BlueCat, and Versa Networks. A detailed analysis of the research findings is available in the report, "Readying Enterprise Networks for Artificial Intelligence." Highlights of the research will also be presented during a free webinar on July 8. About EMA Founded in 1996, EMA is a leading IT research and consulting firm dedicated to delivering actionable insights across the evolving technology landscape. Through independent research, market analysis, and vendor evaluations, we empower organizations to make well-informed technology decisions. Our team of analysts combines practical experience with a deep understanding of industry best practices and emerging vendor solutions to help clients achieve their strategic objectives. Learn more about EMA research, analysis, and consulting services at and follow them on X and LinkedIn. Media Contact:Raleigh GouldEnterprise Management Associates303-543-9500rgould@ View original content to download multimedia: SOURCE Enterprise Management Associates Sign in to access your portfolio
Channel Post MEA
27-02-2025
- Business
- Channel Post MEA
NETSCOUT Unveils New Enhanced Adaptive DDoS Protection Solution
NETSCOUT announced it enhanced its Arbor Threat Mitigation System (TMS) Adaptive DDoS Protection solution with additional AI/ML functionality to better detect and block malicious traffic. Distributed Denial of Service (DDoS) attacks targeting critical IT infrastructure and services have increased by 55% over the last four years. A perfect storm of AI-driven automation, evolving DDoS-for-hire services, augmented IoT botnets, and geopolitical conflicts have changed the threat landscape with more frequent, sophisticated attacks having the potential to do more damage more rapidly. To combat these attacks, organizations, enterprises and service providers require AI/ML-enabled solutions that can continually adapt to threats, using proactive, intelligence-driven security strategies to protect their networks. 'With AI-driven attacks, ransomware, and nation-state threats impacting corporate governance, financial performance, and customer trust, corporate boards expect their IT teams to be proactive in adapting to emerging threats like DDoS,' said Chris Steffen, Vice President of Research – Information Security, Enterprise Management Associates. 'Implementing solutions that can adapt to threats helps minimize that risk.' NETSCOUT utilizes a hybrid AI/ML strategy that combines AI/ML running at scale in the cloud, with supervision, to analyze data collected from an unprecedented 550 Tbps of Internet traffic (almost half of all Internet traffic), along with AI/ML running in our software solutions to enable automated protection from these attacks. This provides a 'best of both worlds' approach – the computational scale of the cloud allows for large-scale analysis of threat data with supervision to ensure accuracy while AI/ML running in our software solutions enables them to leverage that pre-analyzed intelligence to make fast, accurate, automated decisions about what to detect and block. The company's cloud-based AI/ML drives the creation of the ATLAS Intelligence Feed , which delivers unique capabilities in its Adaptive DDoS Protection solutions, arming them with the latest DDoS attack intelligence. The continuous analysis, which is updated multiple times per day, provides insight into the source IP addresses of devices actively conducting DDoS attacks on the internet, novel attack vectors, DDoS attack targets, and other intelligence. This enables Adaptive DDoS Protection to quickly and accurately detect even small direct-path attacks from sampled flow data and send the traffic to TMS for automated blocking. The latest AI/ML-derived ATLAS Intelligence Feed iteration has been augmented with enhanced Geo-IP location functionality that maps IP addresses to geographic locations, enabling faster and more precise identification and blocking of malicious traffic. In addition, the ATLAS Intelligence Feed now includes NETSCOUT's ATLAS tracking of active DDoS campaigns, enabling Adaptive DDoS Protection to automatically detect and block attacks from over 65 known DDoS threat actors carrying out active attack campaigns against a range of targets, including NoName057 and RipperSec. AI/ML technology has also been adopted as part of the Adaptive DDoS Protection solution. New in the latest release is AI/ML-powered source host misuse detection, which enables network operators to track misbehaving subscribers, infected hosts, compromised IoT devices, and other internal attack sources. This new capability makes it easier to detect and block outbound DDoS attacks that can impact service and infrastructure performance and availability as edge connectivity speeds increase. New TMS Source Mitigations enable network operators to redirect and surgically protect against threat activity from specific sources that may be targeting the entire network without requiring fully inline solutions on all network traffic. Service Provider Benefits With updates to NETSCOUT's Adaptive DDoS Protection solution, service providers can better protect their critical infrastructures and the services they provide to their customers. Other key advantages include enhanced availability, reduced downtime costs, less aggravation, and new revenue-generating opportunities. 'With more sophisticated and frequent DDoS attacks, the risks have never been greater,' said Scott Nichols, Chief Commercial Officer at Arelion. 'Through our partnership with NETSCOUT, we're able to deliver industry-leading Adaptive DDoS protection to ensure the best experience possible for our customers.' 0 0
