Auto-sync: wiki-ingest 3 sources (2026-04-16)
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video-source: "nas:///volume2/work/Public Cloud Learning Sessions/CTP _ Topic 13_ Cloud FinOps_ Micro Focus Policies _ best practices to optimize the costs.mp4"
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audio-source: ""
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status: summarized
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status: summarized (Gemini 摘要)
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---
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# CTP Topic 13 Cloud FinOps Micro Focus Policies best practices to optimize the costs
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**Type:** VIDEO | **Category:** 05_FinOps
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**Status:** ✅ 已完成摘要
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**Status:** ✅ 已完成（Gemini 摘要）
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---
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@@ -11,7 +11,7 @@ tags:
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date-added: 2026-04-14
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video-source: "nas:///volume2/work/Public Cloud Learning Sessions/CTP _ Topic 27_ AWS Instance Scheduler.mp4"
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audio-source: ""
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status: summarized
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status: summarized (Gemini 摘要)
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---
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# CTP Topic 27 AWS Instance Scheduler
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@@ -20,7 +20,7 @@ status: summarized
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**Type:** VIDEO | **Category:** 05_FinOps
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**Status:** 🟡 Awaiting Whisper transcription → Summary
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**Status:** ✅ 已完成（Gemini 摘要）
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---
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@@ -11,7 +11,7 @@ tags:
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date-added: 2026-04-14
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video-source: "nas:///volume2/work/Public Cloud Learning Sessions/CTP _ Topic 63_ Optimise resource cost using automation.mp4"
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audio-source: ""
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status: summarized
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status: summarized (Gemini 摘要)
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---
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# CTP Topic 63 Optimise resource cost using automation
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@@ -20,7 +20,7 @@ status: summarized
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**Type:** VIDEO | **Category:** 05_FinOps
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**Status:** ✅ 已完成摘要
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**Status:** ✅ 已完成（Gemini 摘要）
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---
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@@ -1,50 +0,0 @@
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---
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title: "Learning Sessions - FY24Q1 Cost Optimisation - 20230912"
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type: cloud-learning
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source-type: pptx
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category: "DevOps & SRE/05_FinOps"
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tags:
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- Cost-Optimization
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- FinOps
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- FY24
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date-added: 2026-04-14
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video-source: "nas:///volume2/work/Public Cloud Learning Sessions/Learning Sessions - FY24Q1 Cost Optimisation - 20230912.pptx"
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audio-source: ""
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status: raw
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---
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# Learning Sessions - FY24Q1 Cost Optimisation - 20230912
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**Source:** NAS `/volume2/work/Public Cloud Learning Sessions/Learning Sessions - FY24Q1 Cost Optimisation - 20230912.pptx`
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**Type:** PPTX | **Category:** 05_FinOps
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**Status:** 🟡 Awaiting Whisper transcription → Summary
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---
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## 摘要
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> 待转录后由 LLM 生成
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---
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## 关键概念
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-
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---
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## 行动项
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-
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---
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## 相关视频
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> 配对视频笔记链接（生成后填入）
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---
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*最后更新: 2026-04-14*
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@@ -10,7 +10,7 @@ tags:
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date-added: 2026-04-14
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video-source: "nas:///volume2/work/Public Cloud Learning Sessions/Public Cloud Learning Sessions- Best practices for EC2 cost optimization in AWS - 20240529_160242-Meeting Recording.mp4"
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audio-source: ""
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status: raw
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status: summarized (Gemini 摘要)
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---
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# Public Cloud Learning Sessions- Best practices for EC2 cost optimization in AWS - 20240529 160242-Meeting Recording
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@@ -23,28 +23,18 @@ status: raw
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---
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## 摘要
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## EC2 Cost Optimization in AWS: Best Practices
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> 待转录后由 LLM 生成
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Mike Dukes and Steele Taylor, AWS experts, presented a learning session on EC2 cost optimization, covering compute efficiency, Graviton usage, EC2 spot leveraging, and cost-effective container deployments. The session emphasized interactive participation and welcomed questions.
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---
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Efficiency in the cloud involves architectural best practices and leveraging AWS services and instance types for optimal workload performance. Technical advantages include high availability, elastic usage, and innovation adoption. Benefits include cost efficiency, leveraging purchase options, and reducing carbon footprint. *When we start talking about architecting and using best practice efficiency in the cloud, you effectively only pay for what you use when you use AWS.*
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## 关键概念
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EC2 offers over 750 instance types tailored for various workloads. AWS's Nitro system enhances efficiency by externalizing network, storage, and security components. AWS Graviton processors provide price performance benefits. Purchase options include on-demand, savings plans, and spot instances, each suited for different workload types.
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-
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Graviton instances offer up to 40% better price performance than comparable x86 instances. Graviton is based on ARM64 and has extensive software support across Linux OS, ISVs, and open-source software, with sustainability benefits through reduced power consumption. AWS now offers the fourth version of Graviton. Graviton supports various instance types, including compute-optimized, memory-optimized, and general-purpose. AWS services like RDS, Aurora, and Lambda also support Graviton. Migrating to Graviton for services like RDS Aurora is relatively straightforward. *Graviton Free actually uses up to 60% less power consumption than comparable X86-based instances.*
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---
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EC2 Spot instances offer up to 90% discounts compared to on-demand pricing, leveraging spare capacity. Key considerations for Spot instances include fault tolerance, flexibility, and statelessness. Diversification across instance types and availability zones is crucial for Spot usage. Spot instances can be interrupted when capacity is needed for on-demand instances, with notifications provided before termination. Integrations with AWS services like autoscaling, EKS, and ECS support automated responses to interruptions.
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## 行动项
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Spot instances are suitable for web services, containers, HPC batch processing, big data, and CI/CD, while Graviton is beneficial for most of these except stateful services like databases. Spot and Graviton can be used together with containers, provided instance pools are not overly restricted.
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-
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---
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## 相关视频
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||||
> 配对视频笔记链接（生成后填入）
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---
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*最后更新: 2026-04-14*
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Spot Invaders, a fault-tolerant chaos engineering game powered by EKS and EC2 Spot, demonstrates best practices for running resilient applications on EKS while optimizing costs. The game involves shooting aliens to simulate pod failures and whales to trigger spot interruptions, showcasing the ability to maintain service availability despite disruptions.
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@@ -0,0 +1,50 @@
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---
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title: "Public Cloud Learning Sessions- Best practices for EC2 cost optimization in AWS - 20240529 160242-Meeting Recording"
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type: cloud-learning
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source-type: video
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category: "DevOps & SRE/05_FinOps"
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tags:
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- AWS
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- EC2
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- Cost-Optimization
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date-added: 2026-04-14
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video-source: "nas:///volume2/work/Public Cloud Learning Sessions/Public Cloud Learning Sessions- Best practices for EC2 cost optimization in AWS - 20240529_160242-Meeting Recording.mp4"
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audio-source: ""
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||||
status: raw
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||||
---
|
||||
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||||
# Public Cloud Learning Sessions- Best practices for EC2 cost optimization in AWS - 20240529 160242-Meeting Recording
|
||||
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||||
**Source:** NAS `/volume2/work/Public Cloud Learning Sessions/Public Cloud Learning Sessions- Best practices for EC2 cost optimization in AWS - 20240529_160242-Meeting Recording.mp4`
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**Type:** VIDEO | **Category:** 05_FinOps
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||||
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||||
**Status:** 🟡 Awaiting Whisper transcription → Summary
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||||
|
||||
---
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||||
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||||
## 摘要
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||||
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||||
> 待转录后由 LLM 生成
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---
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## 关键概念
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||||
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-
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---
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## 行动项
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||||
-
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---
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||||
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||||
## 相关视频
|
||||
|
||||
> 配对视频笔记链接（生成后填入）
|
||||
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---
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*最后更新: 2026-04-14*
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@@ -10,7 +10,7 @@ tags:
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date-added: 2026-04-14
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video-source: "nas:///volume2/work/Public Cloud Learning Sessions/Public Cloud Learning Sessions - Budget Control - 20240319_160204-Meeting Recording.mp4"
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audio-source: ""
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status: raw
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||||
status: summarized (Gemini 摘要)
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---
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# Public Cloud Learning Sessions - Budget Control - 20240319 160204-Meeting Recording
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@@ -23,28 +23,30 @@ status: raw
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---
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## 摘要
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## Budget Control Automation
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> 待转录后由 LLM 生成
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The SRE Core team (Daniela, Evan, and Alan) presented a learning session on budget control, a new automation providing detailed data to manage budgets and costs within AWS accounts. The session covered the new budget control's value, diagrams, detailed cost reports, AWS budget alerts/actions, and source identity implementation.
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---
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The budget control automation aims to address uncontrolled AWS account sprawl and unsustainable cost reduction efforts. It provides account owners with detailed alerts, including information on account spending and cost drivers, enabling them to identify areas for cost reduction. Enforcement will involve attaching an SCP to block new resource creation. The initial scope is limited to lab accounts, with other accounts continuing to receive standard out-of-budget alerts.
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## 关键概念
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An example alert email includes account details, alert details, warning messages, and detailed reports. There are four types of email alerts: forecast, actual, severe, and enforcement. The alert flow includes forecast alerts at 100% threshold with no action, and actual alerts at 80%, 90%, 95%, and 98% thresholds with escalating recipient lists. At 100%, a severe or enforcement alert is triggered based on a scoring system, with enforcement initially via manual approval and later automated. Budget increases can be requested through an Oli workflow.
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-
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*The source identity must be tracked.* Challenges during development included tracking source identity, customizing AWS budget alerts, choosing an enforcement method (SCP), and providing a grace period before enforcement. Budgets are evaluated every eight hours, and disabled budget actions result in no spend control until the next month. Currently, 80 lab accounts exceed their budgets, and around 100 are expected to exceed 80% of their budget threshold.
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---
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The implementation will be gradual, starting with alerts only on April 1st. Manual enforcement will follow upon FinOps' approval, with automatic enforcement as the next step.
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## 行动项
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## Diagrams and Detailed Cost Reports
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-
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Daniel discussed diagrams and cost reports attached to email alerts, explaining their creation and content. Libraries for lambdas were created to improve code visibility and simplify deployment. The *top services of recent months* report helps managers understand cost drivers, showing the percentage of budget spent on specific services over time. The *top users of current months* diagram allows account owners to monitor daily spending by users. A detailed Excel report provides granular information on resource IDs, creators, and associated costs, separated by month.
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---
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*This is the first time that we were able to get to this level of granularity.* Data for the top services report is generated from Athena, while the user's diagram uses data from Cost Explorer.
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## 相关视频
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## AWS Budget Alerts and Actions
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> 配对视频笔记链接（生成后填入）
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||||
Alan discussed the implementation of AWS budget alerts and actions. The AWS budget service is primitive in terms of customization, so the team had to parse the bodies of the emails received from it. The budget alert system sends messages to an SNS topic, which triggers a Lambda function. The Lambda extracts data from the email and uses it to create a more detailed message. The step function enriches the data with account information, budget details, and owner/manager contacts.
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---
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AWS allows actions to be applied based on alert thresholds. A budget action on 100% triggers either a severe or enforcement email, depending on the scoring system. If budget enforcement is enabled, an SCP is applied to block resource creation. The FINOPS group receives a notification and decides whether to apply the action immediately or negotiate with the account owner.
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*最后更新: 2026-04-14*
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The scoring system and grace period calculations aim to avoid penalizing accounts that slightly exceed their budget near the end of the month. The scoring considers account size and proximity to the end of the month. Smaller accounts have a better grace period.
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FinOps has classified accounts based on cost range. The budgets were last updated on February 23rd. The source identity attribute was implemented to track user activity within AWS accounts, even when assuming different roles. Federated logins use NetIQ access manager to authenticate users and provide access to AWS accounts. The source identity ensures that the original login identity is maintained across role changes, allowing CloudTrail and other services to track user activity accurately.
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@@ -1,24 +1,23 @@
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---
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title: "Public Cloud Learning Sessions - Budget Control - 20240319 160204-Presentation"
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title: "Public Cloud Learning Sessions - Budget Control - 20240319 160204-Meeting Recording"
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type: cloud-learning
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source-type: pptx
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source-type: video
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category: "DevOps & SRE/05_FinOps"
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tags:
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- AWS
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- Budget-Control
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- FinOps
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- Presentation
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date-added: 2026-04-14
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video-source: "nas:///volume2/work/Public Cloud Learning Sessions/Public Cloud Learning Sessions - Budget Control - 20240319_160204-Presentation.pptx"
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video-source: "nas:///volume2/work/Public Cloud Learning Sessions/Public Cloud Learning Sessions - Budget Control - 20240319_160204-Meeting Recording.mp4"
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audio-source: ""
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status: raw
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---
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||||
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# Public Cloud Learning Sessions - Budget Control - 20240319 160204-Presentation
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# Public Cloud Learning Sessions - Budget Control - 20240319 160204-Meeting Recording
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||||
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||||
**Source:** NAS `/volume2/work/Public Cloud Learning Sessions/Public Cloud Learning Sessions - Budget Control - 20240319_160204-Presentation.pptx`
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**Source:** NAS `/volume2/work/Public Cloud Learning Sessions/Public Cloud Learning Sessions - Budget Control - 20240319_160204-Meeting Recording.mp4`
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**Type:** PPTX | **Category:** 05_FinOps
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**Type:** VIDEO | **Category:** 05_FinOps
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**Status:** 🟡 Awaiting Whisper transcription → Summary
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@@ -10,7 +10,7 @@ tags:
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date-added: 2026-04-14
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video-source: "nas:///volume2/work/Public Cloud Learning Sessions/Public Cloud Learning Sessions- Reducing Cloud Costs - 20250318_170100-Meeting Recording.mp4"
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audio-source: ""
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status: raw
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||||
status: summarized (Gemini 摘要)
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---
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# Public Cloud Learning Sessions- Reducing Cloud Costs - 20250318 170100-Meeting Recording
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@@ -23,28 +23,20 @@ status: raw
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---
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## 摘要
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## Reducing Cloud Costs
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> 待转录后由 LLM 生成
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Vinay from the FINOPS team presented a session on reducing cloud costs, focusing on workload and rate optimization. The session covered modernization, right sizing, and best practices for cost reduction.
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---
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### Workload Optimization via Modernization and Right Sizing
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## 关键概念
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Modernization involves using newer generations of services, like EC2 instances. While there's a perception that newer instances are more expensive, the latest families are generally cheaper and offer better performance. *Whenever there's a new family launched by the hyperscale, the latest families are almost cheaper.* However, AWS has slightly changed its pricing model after M6, making M7 and M8 somewhat more expensive. Moving from Intel to AMD can save around 6-10% on on-demand prices for Windows and Linux workloads. Graviton instances can offer even greater savings (20-25% reduction in on-demand cost) for Linux workloads, combined with EDP discounts and commitment plans.
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Upgrading storage from GP2 to GP3 offers a 20% direct cost benefit without downtime. For Amazon EKS clusters, upgrading to the latest versions is crucial to avoid extended support costs, which are significantly higher. *Rather than spending up unnecessary moment on the extended support, you can deploy additional four or five cluster, right.* Spot instances can provide up to 90% discount compared to on-demand, suitable for big data, CI/CD pipelines, web servers, and HPC.
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---
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Right sizing involves identifying the correct resource configuration for workload performance and capacity needs. The EC2 right sizing recommendation report captures CPU usage, memory, and network data to provide recommendations. Configuring instance schedules is useful for non-production environments, allowing instances to be powered on/off based on business hours, potentially reducing costs to 40% of on-demand prices. Identifying and deleting idle load balancers, unassociated elastic IPs, and underutilized EBS volumes are also key to cost savings. Old snapshots and CloudWatch logs also contribute to unnecessary costs. Using cheaper regions like Oregon or North Virginia can reduce costs if there are no specific regional requirements.
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## 行动项
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### Rate Optimization
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-
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Rate optimization involves commitment-based discounts. Hyperscalers offer discounts for committing to resource usage or spending for a term (1-3 years). There are two categories: resource-level commitment (better discount with limitations) and flexible commitment (standard discount with flexibility). AWS offers Savings Plans (EC2 and Compute) and reservations for various services like RDS, ElastiCache, and CloudFront.
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||||
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||||
---
|
||||
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||||
## 相关视频
|
||||
|
||||
> 配对视频笔记链接（生成后填入）
|
||||
|
||||
---
|
||||
|
||||
*最后更新: 2026-04-14*
|
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The rate optimization workflow includes pre-work (right sizing), analysis (identifying workloads requiring 24/7 uptime), communication (sharing details with finance), approval (from account owner), and reporting (monitoring utilization). Only the Phenop's team can implement commitment plans. All commitment plans will be purchased with no upfront payment options only. The minimum transaction value is 5k per annum.
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@@ -0,0 +1,50 @@
|
||||
---
|
||||
title: "Public Cloud Learning Sessions- Reducing Cloud Costs - 20250318 170100-Meeting Recording"
|
||||
type: cloud-learning
|
||||
source-type: video
|
||||
category: "DevOps & SRE/05_FinOps"
|
||||
tags:
|
||||
- AWS
|
||||
- Cost-Optimization
|
||||
- FinOps
|
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date-added: 2026-04-14
|
||||
video-source: "nas:///volume2/work/Public Cloud Learning Sessions/Public Cloud Learning Sessions- Reducing Cloud Costs - 20250318_170100-Meeting Recording.mp4"
|
||||
audio-source: ""
|
||||
status: raw
|
||||
---
|
||||
|
||||
# Public Cloud Learning Sessions- Reducing Cloud Costs - 20250318 170100-Meeting Recording
|
||||
|
||||
**Source:** NAS `/volume2/work/Public Cloud Learning Sessions/Public Cloud Learning Sessions- Reducing Cloud Costs - 20250318_170100-Meeting Recording.mp4`
|
||||
|
||||
**Type:** VIDEO | **Category:** 05_FinOps
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||||
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||||
**Status:** 🟡 Awaiting Whisper transcription → Summary
|
||||
|
||||
---
|
||||
|
||||
## 摘要
|
||||
|
||||
> 待转录后由 LLM 生成
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||||
|
||||
---
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||||
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||||
## 关键概念
|
||||
|
||||
-
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||||
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||||
---
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||||
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||||
## 行动项
|
||||
|
||||
-
|
||||
|
||||
---
|
||||
|
||||
## 相关视频
|
||||
|
||||
> 配对视频笔记链接（生成后填入）
|
||||
|
||||
---
|
||||
|
||||
*最后更新: 2026-04-14*
|
||||
@@ -10,7 +10,7 @@ tags:
|
||||
date-added: 2026-04-14
|
||||
video-source: "nas:///volume2/work/Public Cloud Learning Sessions/Public Cloud Learning Sessions-Storage Cost Optimization - 20240305_160037-Meeting Recording.mp4"
|
||||
audio-source: ""
|
||||
status: raw
|
||||
status: summarized (Gemini 摘要)
|
||||
---
|
||||
|
||||
# Public Cloud Learning Sessions-Storage Cost Optimization - 20240305 160037-Meeting Recording
|
||||
@@ -23,28 +23,24 @@ status: raw
|
||||
|
||||
---
|
||||
|
||||
## 摘要
|
||||
## Storage Cost Optimization
|
||||
|
||||
> 待转录后由 LLM 生成
|
||||
This session covers storage cost optimization best practices across various AWS storage services: Amazon EBS, Amazon EFS, Amazon FSx, and Amazon S3. It includes an optimization example from ADM.
|
||||
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||||
---
|
||||
Key points include choosing the right storage for your workload, considering API costs and data transfer costs in addition to price per gigabyte, and understanding the different tiers available within each service.
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||||
## 关键概念
|
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### Amazon EBS
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-
|
||||
EBS has SSD and HDD volumes. GP3 volumes are recommended as the default for general-purpose SSD due to being 20% more cost-effective than GP2. *With GP3, you can scale IOPS and throughput independently of the volume size.* For migration from GP2 to GP3, automation tools should be updated to create GP3 volumes by default. EBS snapshots have standard and archive tiers, with the archive tier offering 75% lower costs but higher restore times and a 90-day retention period. Automation via Data Lifecycle Management (DLM) or AWS Backup is recommended for managing snapshots, including setting retention policies and migrating to the archive tier.
|
||||
|
||||
---
|
||||
### Amazon EFS and FSx
|
||||
|
||||
## 行动项
|
||||
FSx considerations include data deduplication, compression, and tiering. EFS offers standard, one-zone, and infrequent access tiers, with lifecycle policies to move files between tiers. The infrequent tier has a minimum billable object size of 128KB. EFS archive is a new tier, similar to Glacier, with a 90-day minimum duration and a 128KB minimum billable object size. FSx for NetApp ONTAP has SSD and HDD tiers (capacity pool), with automatic tiering between them.
|
||||
|
||||
-
|
||||
### Amazon S3
|
||||
|
||||
---
|
||||
Choosing the right storage class is crucial for S3 cost optimization. S3 Standard is for frequently accessed objects, with no retrieval fees, minimum retention, or minimum billable object size. Glacier tiers (Instant Retrieval, Flexible Retrieval, Deep Archive) are for rarely accessed data, with varying retrieval times and costs. Intelligent Tiering automatically moves data between tiers based on access patterns, with no transition fees between tiers within Intelligent Tiering. *With intelligent hearing we can automatically move data from warmer to colder color storage tiers and it will be based on the object less access data.* Lifecycle policies can transition objects between tiers, expire non-current versions, and delete incomplete multi-part uploads. Data transfer charges should be considered, and PrivateLink can be leveraged to stay within the AWS network. Storage Lens, CloudWatch, S3 Inventory, and access logs can be used to monitor and optimize S3 usage.
|
||||
|
||||
## 相关视频
|
||||
### ADM Optimization Example
|
||||
|
||||
> 配对视频笔记链接（生成后填入）
|
||||
|
||||
---
|
||||
|
||||
*最后更新: 2026-04-14*
|
||||
ADM migrated NetApp file shares from on-premises to AWS. The initial migration to OpenZFS was inefficient. A second migration to a self-managed NetApp on EC2 instances incurred high data transfer costs. The final migration to AWS FSx for NetApp ONTAP resulted in a 60% cost reduction.
|
||||
|
||||
@@ -0,0 +1,50 @@
|
||||
---
|
||||
title: "Public Cloud Learning Sessions-Storage Cost Optimization - 20240305 160037-Meeting Recording"
|
||||
type: cloud-learning
|
||||
source-type: video
|
||||
category: "DevOps & SRE/05_FinOps"
|
||||
tags:
|
||||
- AWS
|
||||
- Storage
|
||||
- Cost-Optimization
|
||||
date-added: 2026-04-14
|
||||
video-source: "nas:///volume2/work/Public Cloud Learning Sessions/Public Cloud Learning Sessions-Storage Cost Optimization - 20240305_160037-Meeting Recording.mp4"
|
||||
audio-source: ""
|
||||
status: raw
|
||||
---
|
||||
|
||||
# Public Cloud Learning Sessions-Storage Cost Optimization - 20240305 160037-Meeting Recording
|
||||
|
||||
**Source:** NAS `/volume2/work/Public Cloud Learning Sessions/Public Cloud Learning Sessions-Storage Cost Optimization - 20240305_160037-Meeting Recording.mp4`
|
||||
|
||||
**Type:** VIDEO | **Category:** 05_FinOps
|
||||
|
||||
**Status:** 🟡 Awaiting Whisper transcription → Summary
|
||||
|
||||
---
|
||||
|
||||
## 摘要
|
||||
|
||||
> 待转录后由 LLM 生成
|
||||
|
||||
---
|
||||
|
||||
## 关键概念
|
||||
|
||||
-
|
||||
|
||||
---
|
||||
|
||||
## 行动项
|
||||
|
||||
-
|
||||
|
||||
---
|
||||
|
||||
## 相关视频
|
||||
|
||||
> 配对视频笔记链接（生成后填入）
|
||||
|
||||
---
|
||||
|
||||
*最后更新: 2026-04-14*
|
||||
Reference in New Issue
Block a user