Every provider has an attribution mechanism. AWS has Inference Profiles. Azure tracks by deployment. GCP has request labels. But each one has a blind spot.
This comprehensive guide covers right-sizing, smart code optimization, event filtering, and efficient monitoring techniques. Learn how to reduce Lambda costs without sacrificing performance, implement best practices, and avoid common pitfalls. Perfect for developers and architects looking to build cost-efficient serverless applications.
AWS NAT Gateway is essential for managing traffic from private subnets, but it can silently inflate your cloud costs through data processing fees. Every AWS service call—whether to S3, DynamoDB, or other services—incurs a $0.045/GB charge when routed through NAT Gateway.
Each AWS service call from private subnets could be adding unnecessary NAT Gateway charges ($0.045/GB) on top of standard data transfer fees. With 50TB monthly traffic, that's $2,250 in avoidable costs. Analysis of how VPC endpoints eliminate this double-charging, with performance implications and implementation patterns.
As your startup scales on AWS, managing access control becomes crucial. This blog post provides a roadmap for securing your cloud environment. You'll learn about the limitations of basic IAM users, the benefits of centralized identity management, and the capabilities of AWS IAM Identity Center with Just-In-Time access.
From mere labelling in 2010 to the sophisticated tagging services of today, AWS tagging has seen a rapid evolution. These updates have provided users with additional functionality, greater control over their resources, and more effective monitoring, auditing, and management of their AWS infrastructure.
It is critical to understand that almost anything in the cloud can assume an identity. Resources can have direct and indirect relationships, some of which are not obvious.
Congratulations on your launch. I'm don't have technical background to understand the nitty gritty, but reading through all the comments itself is an immense learning on the topic.Good luck.
Currently it is third party service collecting the data, we reduct the sensitive information. The data is encrypted at rest and we follow best security rules.
Though our existing model is SaaS based, we are contemplating to separate the control plane into SaaS model, while keeping data plane within the users account. We want to work with our users feedback for this.
Please do try and share your valuable feedback.Thanks!
I’m not surprised you asked how CloudYali is different from AWS Config. We have been asked this earlier as well.
As we know AWS Config, when debuted in 2014 it promised to be the configuration auditor for AWS. The mandate for any team working in AWS workload management, is security and cost effectiveness along with operational efficiency. This requires a great deal of visibility into the cloud workloads. These workloads consists of cloud assets (or resources) from multiple AWS services. As a configuration auditor, AWS Config is supposed to provide a complete visibility into the cloud assets, keep the configuration history of changes and help in achieving the regulatory compliance.
Today AWS has more than 200 services, and more than 500 cloud assets types. In 2017, AWS Config supported ~26 services and 72 resource types. In 2021, the coverage has reached barely 103 resource types. This is ~20% coverage across all the asset types. These assets have relationships which may cross the service boundaries. These relationships are important to be understood, from security point of view (lateral movement attacks). Similarly you need to know about all your assets from cost point of view. You never know if someone accidentally started any expensive service, say macie and you realise it only when the monthly bills arrive. Problem with AWS Config is lack of coverage and even slower addition of newer resource types into coverage.
Yet another issue is usability. AWS Config is a regional service, which needs to be configured across all regions and accounts. This is a sizeable effort. Recently only AWS Config started with Organizations support. When you’re in midst of incident resolution, the important t for any cloud team is access to historical information about the configuration changes. AWS Config UI and CLI is not something you want to deal with at that moment.
For CloudYali, the mission is to provide visibility across all the cloud with usability in mind. CloudYali works on multiple accounts and all regions by default. This means, by default you are looking at the cloud assets across your whole cloud. We have currently added a support for ~ 250 asset types (and we will keep adding).
CloudYali, also maintains the lifetime of the assets, and the history of configuration changes. It is like applying version control to the cloud. The configuration changes are visualised on the timeline, where you can choose to see configuration attributes at any given time. We clearly mark the assets as Live/Active or Deleted if asset no longer exists. It is also possible to filter assets based on the accounts, regions, or time duration so that it is easier to pinpoint assets. This makes troubleshooting easier for cloud operations. Consider for example, rules in load balancer, min/max for auto-scaling group. These things are often changed manually during production issues and if you don't have backups, it's quite easy to mis-configure and then spend time trying to recall previous values. CloudYali intends to be helpful in such scenarios.