If you’re currently using Spot to save on your ASG costs, you’re familiar with the complexity and time needed to cost-optimize your commitment usage and choosing the best Spot instances for your workloads. 

Compute Copilot was created to make it easy to save, bringing Spot market insights and awareness of your commitments to your Mixed-Instance ASGs. It automatically and continuously tunes your ASG configurations to ensure you’re (1) always using the right amount of Spot, and (2) always on the most cost-effective and reliable option available, gracefully replacing your nodes before termination.

And because it’s built on your existing AWS-native ASGs, it’s ultra-easy to onboard. Simply plug it in to effortlessly run mission-critical workloads with peace of mind that you are scheduled on the most cost-optimized and stable option at all times. 

New Mixed-Instance Policy & Lifecycle Hook Support

For hassle-free savings on the full range of your ASGs, Copilot now optimizes: 

• ASGs with Mixed Instance Policies — Launch multiple instance types and On-Demand Instances and Spot Instances within a single Auto Scaling group.
• ASGs with Lifecycle Hooks — Create solutions that are aware of events in the Auto Scaling instance lifecycle, and then perform a custom action on instances when the corresponding lifecycle event occurs.

It just takes a couple of quick tags to onboard and start realizing effortless Spot savings on all of your ASGs.

At nOps, our mission is to make it easy for engineers to optimize cost. Learn more about how Compute Copilot can help you save while freeing up your time to focus on building and innovation. 

How It Works

The below diagram provides additional information on how Copilot optimizes your ASGs.

ASG launches a new on-demand instance

Lambda intercepts the EC2 Instance State-change Notification event from EventBridge

If the created instance is not protected from termination and should be replaced, Compute Copilot performs the following steps:

1. Copy the Launch Template or Launch Configuration from the ASG launch template
2. In the copied Launch Template, modify Network Interfaces, Tags, Block Device and/or Mappings from the instance Launch Template or Configuration if needed
3. Fetch recommended instance types from nOps API
4. Request Spot Fleet with the copied Launch Template and recommended instance types
5. Once the Spot request is fulfilled, get the Spot Instance and wait for it to its state to be Running
6. Attach the created Spot Instance to the ASG
7. Wait for the attached Spot Instance’s state to be InService
8. If there is a lifecycle hook for termination for On-Demand, the On-Demand will go through the lifecycle hook action for termination
9. Terminate the On-Demand instance
10. If there is a Mixed-Instance Policy, modify the percentages of On-Demand and Spot accordingly.  

For more information, you can also consult the documentation.

With nOps, it’s as simple as integrating your existing utilization and monitoring tools to start right sizing and shrinking your AWS bill. 

Today, we’re announcing a new feature helping you save more by effortlessly right sizing even the most complex of instances. nOps now supports: 

EBS Encryption: Right sizing instances with security and compliance requirements is normally a time-consuming and complex process, involving stopping the instance, fetching a key, de-encrypting, right sizing, re-encrypting, and restarting each instance. nOps now seamlessly integrates with AWS's key management to put it all on autopilot, making it extremely easy to right size. 

Hibernation: nOps now automatically right sizes Hibernation enabled instances, for occasions when you need to save the state of your EC2. Delegate the normally complicated and annoying process of disabling each instance without losing any data, right sizing, and restarting  — freeing up your time to build and innovate.

Let’s take a look at the benefits of automated right sizing with nOps. 

• Fully trustworthy recommendations. Often, engineers don’t implement right sizing recommendations because they don’t trust them. By automatically collecting comprehensive data on your memory, CPU, storage, and networking through your existing monitoring solution (Datadog, CloudWatch…), nOps right sizing recommendations are highly trustworthy.

Visualize right sizing recommendations in an easy-to-scan dashboard.

• Significant time savings. Simply integrate your existing monitoring solution, review recommendations, and one-click apply via automation. nOps makes it pain-free to right size in seconds to eliminate underutilized and idle resources driving unnecessary AWS costs.
• Expanded cost savings. With the new release, you’re no longer limited to saving on “vanilla” EC2 — you can right size Encrypted and Hibernated instances for more effort-free AWS savings.

nOps was recently ranked #1 in G2’s cloud cost management category. Join our customers using nOps to slash your cloud costs and leverage automation with complete confidence by booking a demo today!

Today, we’re announcing Configure-by-Tag: a new feature making it as easy as possible to onboard to Compute Copilot for ASG and start saving. 

The feature brings you:

• Effortless integration via any IaC tool. IaC integration eliminates all the manual work of managing ephemeral ASGs through redeployments. Once you onboard with a quick tag, you’re completely done — create, destroy, recreate ASGs, and they will be automatically configured for Compute Copilot.

• Centralized management of configurations. Configure-by-Tag makes bulk management of ASG configs simple. A single template can manage all the configuration options for as many ASGs as desired.
• Automatic Spot savings. Once you Configure-by-Tag, Compute Copilot for ASG will automatically put you on the most stable and cost-optimized Spot instance types — for effort-free continual cost reduction. 

You can observe instance replacements and ASG configurations reflected in the UI. For more specifics on how it works, check out the full documentation.

At nOps, our mission is to make it easy for engineers to cost optimize by seamlessly integrating with your preferred tools and services.

Learn more about how Compute Copilot can help you save while freeing up your time to focus on building and innovation. 

Compute Copilot for EKS integrates with Karpenter to automatically reduce your AWS bill. 

It now supports YAML configurations, in the latest update for flexibility and ease of use. In response to customer request, this release offers:

Effortless onboarding. YAML configuration makes it ultra easy to onboard your Karpenter-managed cluster to Copilot via UI or API. Simply import your current configurations to migrate to modern Karpenter and put your node provisioning on autopilot.

Full control. Whether you want to delegate your configurations to nOps or exercise granular control, YAML configuration unblocks all Karpenter-supported configuration options.

Rightsizing recommendations are frequently wrong. Reliable recommendations require granular historical data on memory, utilization, network bandwidth, volume size, and more. This data is difficult to collect and analyze. As a result, engineers don’t trust recommendations are accurate, and don’t act on them. 

Acting on recommendations is complex and incredibly time-consuming. Cumbersome resource investigation, ticketing processes, manually editing Terraform and more means rightsizing initiatives can be a multimonth IT resource time sink.

Datadog and nOps to the rescue

To make rightsizing easier and more effective for teams, Datadog and nOps have partnered together. Via a one-click integration with no additional costs or steps, nOps builds on the end-to-end visibility provided by Datadog to revolutionize your rightsizing and commitment management.

Datadog’s cloud monitoring and analytics provides engineers with real-time coverage of resource-level insights such as memory, CPU, and storage — granting nOps full visibility into the exact data needed for 100% accurate rightsizing recommendations. 

nOps’s automated FinOps platform then makes it insanely easy for engineers to take action. Via integration with your tools and frameworks (Terraform, Eventbridge…), nOps fully automates months of work to apply recommendations into mere seconds. 

Here’s how this natural partnership is changing the game. It grants you:

Complete Rightsizing Confidence. Datadog’s comprehensive logging and monitoring data is fed into nOps’s state-of-the-art ML engine. These data-backed recommendations are visualizable in an easy-to-scan dashboard which proves reliability and accuracy to engineers beyond a shadow of a doubt — giving them the confidence to act on recommendations.

Hours of Time Savings. With the platform, it takes five seconds to make a changeset, accept the changeset, and push it out. nOps automates away all the work and complexity, freeing up engineers to focus on other meaningful projects. One click to accept the recommendation and you are done.

Vast Cost Savings. When engineers don’t act on rightsizing recommendations, underutilized and idle resources continue to drive unnecessary AWS costs — leading to thousands in missed savings accumulating every day. nOps make it completely pain free and effortless for engineers to actually act on recommendations for up to 50% in immediate cost savings. 

Hands-off commitment management. Once you accept rightsizing recommendations, nOps automatically provisions and deprovisions commitments into your environment. As a result, you benefit from the savings of SPs, with all the flexibility of on-demand.

nOps was recently ranked #1 in G2’s cloud cost management category — and together with Datadog, the savings are reaching new heights.

nOps Business Contexts is replacing Cloud Resource Cost as your tool to continuously access and allocate 100% of your AWS cost in real time.

Cloud Resource Cost is currently found under Dashboard -> Cost -> Coud Resource Cost. Business Contexts is currently found under Dashboard -> Business Contexts.

What are the benefits of nOps Business Contexts?

• Massively scaleable and faster analysis for customers of all sizes. Now leveraging Apache Druid’s lightning processing and distributed architecture, the platform brings you real-time actionable insights in unprecedented detail.
• New hourly resolution of spend data for detailed analysis. Business Contexts ports all the best-loved features from Cloud Resource Cost, now with new hourly resolution.
• Deep integration with our Cost Allocation feature (showbacks, chargebacks, and tagging).  nOps is now a single repository, data-centralized platform, granting you the ability to break down your daily spend by engineering service, day by day and hour over hour, across your entire AWS organization.

• Powerful reporting to track expenses and share with stakeholders. Don’t settle for complex and static dashboards. Business Contexts provides up-to-the-moment, intuitive reports to visualize your cloud infrastructure and costs.

Cloud Resource Cost will be sunset on Monday, October 9, 2023.

Economic uncertainty is increasing the pressure to reduce cloud spend, and companies are looking for ways to optimize their resource management. As the industry shifts towards Kubernetes, EKS is one of the biggest expenses — and thus a low-hanging fruit for optimization.

Kubernetes configurations are often set once and not reassessed for months or until there is a problem, leading to waste and inefficiency. As a result, Engineering and DevOps leaders are increasingly turning to solutions that can automate decisions in real time, such as Vertical Pod autoscaler and AWS Karpenter. Karpenter is an open source solution that frees users from node groups and autoscaling constraints, allowing resources to be provisioned according to actual usage.  

The problem is that Karpenter is often tuned as a one-and-done exercise. However, your ecosystem is dynamic — and so is market pricing. 

That’s where nKS (nOps Karpenter Solution) comes in, automatically and constantly tuning your configuration for the best price and availability. It is the first, easy-to-use UI for Karpenter.

As a result, engineering teams can take advantage of Karpenter’s more effective and granular scaling functionalities with a fraction of the effort. nKS constantly ensures you are scheduled on the most cost-optimized and stable option — automatically updating your provisioning on the fly if not. Customers are saving 50% or more on EKS costs with nKS.

nKS now supports multiple provisioner configurations, in the latest update for even more flexibility and ease of use. In response to customer demand, this release offers:

More control over the environment. nKS can accommodate a wide variety of use cases —supporting existing constraints or the demands of complex, multi-cloud architectures.

(Manage and configure your provisioners directly from nOps).

Increased time savings. nKS makes it pain-free to import your current configurations, migrate to modern Karpenter, and put your node provisioning on autopilot.

Here’s more on why engineering teams are delegating their cloud provisioning to nKS. The tool:

• Automatically schedules EKS resources to available Reserved Instances, Savings Plans, and Spot
• Monitors pricing and your entire AWS ecosystem continually, ensuring maximum savings and availability
• Predicts Spot terminations 60 minutes in advance using ML

The best part? With nKS, you don’t spend — you only save. We are the first cloud management platform that charges based on a fraction of the customer’s savings.

Join our customers already using nKS to slash cloud costs and run Spot with complete confidence by booking a demo today!

One of the most prominent challenges our customers encounter revolves around understanding and managing their cloud expenses. This issue stems from inadequate visibility and intricate cost attribution, resulting in user confusion. While the cloud provides scalability and flexibility, it also presents new challenges, including limited resource visibility  into resource usage.

In a world where workloads constantly scale up and down, and cloud billing occurs hourly in units of milliseconds, effectively analyzing, forecasting, and optimizing your cloud environment based on daily spend is nearly impossible.

To address these challenges, we are thrilled to announce the launch of our new feature – “Hourly Granularity,” into cloud cost analysis of AWS data. This feature provides cloud users with access to hourly usage graphically, offering enhanced cost visibility, cost allocation, and predictive analysis.

The Hourly Granularity is set to revolutionize cloud visibility, offering businesses enriched monitoring capabilities, real-time insights, and resource optimization. An exceptional aspect of nOps' Hourly Granularity is its capacity to monitor costs on an hourly basis within a 30-day timeframe, contrasting with the traditional 14-day period on AWS. This expanded scope offers a richer and more comprehensive comprehension of your expenses, greatly improving your ability to monitor costs astutely and strategize effectively.

Moreover, nOps' "Cost Allocation" feature empowers users to establish filters that significantly enhance the efficiency of tracking various categories, far surpassing the manual approach. For instance, with specified filters, you can skillfully analyze the distinct services contributing to expenditures. Furthermore, the integration of "Cloud Cost Analysis" allows you to interactively view real-time costs directly on the nOps dashboard, delivering unparalleled insights.

To efficiently monitor costs on an hourly basis and allocate your cloud costs across suitable business units in nOps, see nOps Business Contexts

In addition, addressing underutilization stands as a paramount challenge at nOps. Given AWS' billing model, commitments are allocated in hourly segments, rendering a daily cost overview insufficient for grasping the dynamic commitment patterns that shift by the hour. By adopting an hourly resolution, users gain a magnified perspective into their resources, allowing for a more insightful analysis.

The visual depicts the "Daily View" of resource utilization spanning a two-day timeframe. The graph portrays a notably steady and elevated usage level, implying the feasibility of opting for a higher usage limit. However, it's essential to note that this portrayal does not precisely mirror the genuine usage pattern.

Whereas this visual depiction illustrates the hourly distribution of resource usage over the same two-day timeframe. The graphical representation vividly underscores the irregular patterns characterizing the usage trend. Opting for the elevated usage threshold recommended by the daily overview may lead to incurring avoidable cloud expenses during intervals of notably diminished usage that falls below the prescribed limit.

With an hourly perspective, gaining a comprehensive grasp of your overall EC2 usage and its hourly fluctuations becomes notably simpler. Consider this scenario: under the daily view, if a user commits to covering usage costs at a $2.75 per hour rate and later observes a decrease to $1.50 per hour, they remain bound by the higher rate, even during periods of lower usage. In contrast, the hourly view offers a finer understanding of resource consumption, leading to informed decisions and substantial savings.

The Hourly granularity serves as a foundation for data-driven decision-making, fostering enhancements in both performance and cost-effectiveness. This method ensures that each choice is rooted in a comprehensive understanding of the organization's financial well-being.
It empowers organizations with the precision to forecast expenditures, enabling seamless adoption of FinOps, curbing cloud waste, and fostering alignment between procurement and engineering teams.

It also functions as a robust troubleshooting tool for engineers, granting them the ability to delve into service usage, performance, cost allocation, and hourly-based cost concerns. It facilitates the identification of hourly resource usage cycles, thereby assisting in well-informed determinations about when to activate or pause resources based on usage patterns.

To read to know about how it works, click here. Try nOps Business Contexts today! 

For more information, visit the website

This week, nOps launched a new feature nSwtich Tag-Based Scheduling. Schedule-by-Tag empowers users to take full control of their cloud costs by aligning resource usage with demand.
This innovative feature allows you to schedule resources by adding a tag, empowering your developers to manage resource tags effortlessly using any Infrastructure-as-Code solution.

To access Tag-Based Scheduler in nOps and automatically pause resources during off-hours, explore nSwtich.

How Does It Work?

Tag-Based Scheduling leverages the power of AWS EventBridge to automatically pause instances such as EC2 instances, AutoScaling groups, RDS instances, RDS clusters, EKS node groups, or EKS clusters when they are not in use. 

With Schedule-by-Tag, managing your AWS resources becomes simplified. You can create schedules without initially attaching resources, making it a seamless process. The key lies in copying the tag value generated by our service and adding it to the desired resources using either the AWS console or popular Infrastructure-as-Code frameworks like Terraform.

nOps continuously monitors the tags assigned to your resources and automatically adds them to the Scheduler as soon as it detects them, ensuring optimal cost savings and resource utilization.

Take control of your costs by aligning resource usage with demand. Users can set up templates to automatically add dev, QA, or staging resources to a pre-defined schedule and ensure that they’re only being charged for resources when your global teams need to use them.

To learn more about nOps nSwtich Tag Based Scheduling and how it can help you optimize your cloud costs, you can explore Automatically Reduce Dev and QA Costs by Creating Tags Based Schedules. 


You can read more about nOps and its cloud cost management solutions at nOps.io. 

This week, nOps has launched an advanced Cost Analysis feature that offers flexible filters and a comprehensive view of your resource spending. With this feature, you can now gain greater visibility into the true cost of resources, including commitments like RI and Savings Plan, and analyze how your commitment impacts or contributes to your actual resource cost.

There are three cost types to choose from - Unblended, Blended, and Amortized - allowing users to switch between them effortlessly to enhance visibility. This means users can easily compare and contrast different cost types to get a better understanding of their cloud spend.

View your amotorized spending by resources so that you can see the true cost of resources including commitments like RI and Savings Plan. 

Amortized view provides a clear and accurate view of the true cost of a resource by factoring in reservations and savings plans. With this view, you can easily track your resource spending on a daily basis and gain insights into how your commitments impact your actual resource cost.

To efficiently allocate your cloud costs across suitable business units and business outcomes in nOps, see nOps Business Contexts

One of the key advancements of this feature is the elimination of limitations on the number of resources, making it possible to monitor all your resources without any restrictions. With nOps' Enhanced Cost Analysis, you can easily track your AWS spending, optimize your resource usage, and achieve greater cost savings.

Cloud spend analysis feature provides users with unparalleled control and customization options. With this feature, users can now easily include, exclude or match their cloud spend based on filter dimensions, such as support, marketplace, or RI fees, and gain a comprehensive view of their cloud costs. You can dive deeper into their spend data by leveraging various dimension filters and visualizing cost distribution across Daily, Weekly, Monthly, and Quarterly data resolutions. And, as a bonus, nOps will soon be adding Hourly data resolution

The nOps' Cost Allocation Showback Values feature, you can easily track your AWS expenses over time in the context of your business. With the ability to match, include, exclude, and use fuzzy or pattern matching, you can create custom filters that fit your specific needs.

Filter out costs such as Support and RI fees to gain a clearer picture of your expenses. Save and share customized reports with ease using any combination of filters and cost allocation showbacks.

Experience the convenience and flexibility of nOps' Cost Allocation Showback Values and streamline your AWS expense tracking today To learn more about nOps Cost Analysis cost visibility recommendations, Try nOps Business Contexts today! 

For more information, visit the website