What does AWS CCP stands for

AWS CCP stands for certified cloud practitioner. It is one of the entry points in the cloud journey. This certification is for the person who wants to know about the services of Aws. The cost of the exam is 100 $. You can give a practice exam before the actual exam of Aws that costs you only 20$. The passing percentage in this exam is 70%.

AWS certification is valid for three years.

Eligibility Criteria

• Aws recommends that Candidates should have at least 06 months of experience with the AWS cloud. It is not necessary to complete six months. You can give according to your preparation.
• Candidates should have a basic understanding of IT services and their uses in the AWS Cloud platform.

Exam Syllabus

This exam consists of four parts:

Preparation Strategy.

For clearing this exam you need 12-15 hours of self-study and 5-6 hours of revision. Here is the four-point strategy which I followed to clear the exam.

• First of all, you should cover the videos provided on the AWS learning platform. This course helps you to gain a basic understanding of AWS services easily. The link to Aws learning platform
• Now you should try mock papers available on Udemy. Practice these papers until you get 90% in each exam. Read the explanation of each question to get a better understanding of the Aws services. You will get 60-70 % of questions from these papers, not the exact questions but the logic will be the same. The link of practice papers
• If you do not want to purchase these practice papers then read the Aws white papers which are available on the AWS learning platform.
• This exam is all about retention about the AWS services usage. You will get scenario-based questions in the exam. You should revise min 02 times about all services.

Booking the AWS CCP Exam

1. Log in to your AWS certification account. 
2. Once you are successfully logged in, click the Upcoming Exams menu link.
3. After scrolling down on this page you will see two options 1. Schedule with Pearson Vue 2. Schedule with psi.
4. To Book your exam with Pearson Vue you will have to follow these steps.
   1. In the Pearson Vue console, you will see two options 1. At test center 2. At the office or home. Choose option 2 if you want to give a test from home. Then click on the next. On the next page, you will find the Pearson Vue agreement. Read the agreement and then check all the boxes and click on agree.
   2. After this, you will get the option to choose your preferred language. Then click on Next.
   3. After this, you will see your exam details. In the confirmation tab, you can manage your test. Click on Next.
   4. Find an appointment according to your availability.
   5. Pay the fees for your exam. If you have the coupon/vouchers you can apply the same in the voucher/promotion section to get extra benefits. To see your benefits click on benefits which is available on the same tab where the Upcoming Exams link was there. You have to open the international payment option of your card.
   6. Congratulations! You have successfully booked your examination. All the best for the exam.

Last-Minute Tips

• You will get mail from Pearson Vue for the system check requirement. You must check this requirement on the same system on which you want to give the test.
• You should avoid giving tests on the company-provided laptops generally there is more restriction on this type of laptop.
• Revise the important topic one day before the exam.
• Practice mock papers before the actual exam to gain confidence.
• Take a proper nap before the test.
• On the exam, day log into the system 30 mins before the scheduled appointment.
• Clear your table before the exam. No notes, no monitor, no electronic equipment. You can place your mobile phone at a one-hand distance from you. You will be provided an online proctor who will be in touch with you during the whole session of the exam.

Don’t miss these topics

In this section, I will cover the topics from which you might get questions in aws ccp. Here are the ten most important topics:

• Aws Ec2 pricing model and instance types: Pricing model difference, instance application, message queuing.
• Storage Services: Difference between storage services and their application in real life.
• Aws global infrastructure: Cloud front( in details), Edge location. Application-based question. When and where to use it.
• Shared responsibility model: You must be clear about the Aws responsibility, user responsibility, and the shared responsibility. You will get 3-4 questions on this topic.
• Aws organization: You will get direct questions from this section. It is an easy and scoring section.
• Aws budget and cost explorer 
• The monitoring system of Aws: Cloud watch, cloud trail, and trusted advisor check are the important topics in this section.
• Aws Waf architecture: Read Aws whitepapers carefully for this section.
• Various services: Service health dashboard, personal health dashboard, marketplace, migration strategy.
• Miscellaneous services: Aws glue, code commit, quick sight, technology partners, abuse team, data pipeline. For all this, you must read 3-4 lines about each from Aws white papers.

5 Point Strategy to be followed in AWS CCP

1. Read the full question: Read the question carefully and catch the keywords or phrases from the question. If you miss this then it is a high chance that you will mark the incorrect response.
2. Predict the answer before reviewing the response options: If you find your predicted answer in the options then it is a high chance that you will mark the correct answer as it avoids the distraction from the wrong responses. But you should also check the other options for confirmation.
3. Eliminate incorrect options: Before selecting the options try to remove the incorrect option which you believe is incorrect. This strategy helps you with multi response questions.
4. Time is not a barrier in this examination: 90 minutes is more than enough for this exam. You should check your answer twice before submitting your final response.
5. Mark for review and flag the questions: In first go attempt the question in which you are confident and mark the question for review in which you are not sure and solve these questions only in the second attempt.

Conclusion

AWS CCP is an easy exam. You must be clear about cloud fundamentals. It is just the tip of a glacier in the AWS field. Best of luck for your cloud journey .

Continue exploring at Teknonauts.com

Vasu Goyal

Vasu is currently working as a Software Engineer in Incedo Inc and got himself Aws Certified cloud practitioner. He is a self-starter who is excited about different technologies.

I have recently cleared Oracle Cloud Infrastructure Architect Associate (1Z0-1072-20) exam. Just wanted to share my experience. Here are step by step guide that I followed to clear this exam

1. Go through the complete course given on page ( Oracle Cloud Infrastructure Architect Associate ) –

Oracle Cloud Infrastructure Architect Associate by Rohit Rahi

2. Do some hands as suggested by Rohit Rahi (focused on Oracle Cloud Infrastructure Architect Associate )

3. Take practice exam from Udemy ( Oracle Cloud Infrastructure Architect Associate ) –

Practice Test for Oracle Cloud Infrastructure Architect Associate on Udemy

4. Do the practice test available in the first link and score more than 80%

You are ready for the exam Oracle and become Oracle Cloud Infrastructure Architect Associate. Good luck!

Here are some notes, I took during my preparation for Oracle Cloud Infrastructure Architect Associate

Awadhesh Pratap Dwivedi

Awadhesh Pratap Dwivedi is an IT industry leader with over 13+ years of experience. He is excellent at providing an easy solution to complex business problems with his tremendous problem-solving skills. Currently, he is working with Oracle as a Principal Solution Engineer.

teknonauts.com/

What is Predictive Maintenance ?

In very basic terms, Predictive maintenance is the application of machine learning algorithms in industrial machine so that they have predictive capability. Predictive maintenance has always focused on how to predict when certain conditions are going to occur and when machines will fail.

With the advancement in the field of machine learning & ability to do it at a large scale, we have now many use case where we can apply it. It is not just reserved for a few organization any more. It is now available to all those industries which have a heavy use of assets or machines.

What is the Need of Predictive maintenance ?

The interest to have predictive capabilities is growing in the organization is growing day by day because:

1. Manufacturers need to know when a machine is about to fail so they can better plan for maintenance. For example, as a manufacturer, you might have a machine that is sensitive to various temperature, velocity, or pressure changes. When these changes occur, they might indicate a failure.
2. With predictive maintenance in place you can do a load balancing among your machineries. For e.g. You have 100’s of motor installed in your plant, only 20% of them are running in peak times, With relevant amount of statistical model you can plan so that all motor run in equal amount.
3. Cost reduction: Since you can plan in advance, you do not have to pay yearly maintenance or reactive maintained cost. Some machines or asset does not need maintenance every year but based on amount of usage but industries still pays annual AMC to the vendors. This cost could be reduced.

Evolution of Maintenance

Reactive maintenance

In this type people used to fix any trouble in machine only when its is broke down.

Preventative maintenance

In this people used to do maintenance on a fixed schedule basis. Similar to your car service annually based on running km say 10000 km or every 12 months. The key here is you define a certain threshold.

Problem here was

1. you often end maintaining the machines which doesn’t require any maintaining or you would find things break down before the schedule threshold.
2. Also, Manufactures took this type of maintenance for their advantage, they set such limits so that they can limit the risk & increase the profit by the warranty clauses.
3. Quite often assets are maintained on a higher frequency than what is required & this would create maintenance induced failures in machinery.

Manual predictive maintenance

AS technology advancement took place, engineers started to take measurement of parameters affecting the condition of an asset. They used vibration monitors or ultrasonic devices or other means. You created a predictive maintenance capability but it was still manual. This is present in our world from sometime but it often required operator going out and taking measurement. They have to physically go out and take readings, capture that data and plot it out.

It takes hours of effort of creating a spreadsheet, then on basis of their analysis they would come up with predictive maintenance schedule. It was a great idea but execution was done on an adhoc basis.

IoT-based predictive maintenance (where we are right now)

With IOT in place the way we look at predictive maintenance has changed, you can now monitor your assets in real time at a very low cost that sends data to an algorithm on a continuous basis. Then algorithm can take a decision whether there is something wrong happening with the machine or not. Also predict when the maintenance needs to be done.

That is where predictive maintenance is going now with what we call IoT-based predictive maintenance.

You can then schedule maintenance based on that data.

How to get started ?

To get started you need to follow some below key points:

1. Start analyzing your assets from parameter point of view, means which parameter affect the health of your machine. E.g. identify key variables for a battery, we get temperature & voltage.
2. Identify the sensors which are capable of monitoring those variables. In our case we take temperature sensor and voltage sensors.
3. Identify your gateway to aggregate the sensor data.
4. Select your IOT to platform to collect the data and analyze it.
5. Choose your machine learning algorithm  as per your use case.

Prediction, sometimes referred to as inference, requires machine-learning (ML) models based on large amounts of data for each component of the system. The model is based on a specified algorithm that represents the relationships between the values in the training data. You use these ML models to evaluate new data from the manufacturing system in near real-time. A predicted failure exists when the evaluation of the new data with the ML model indicates there is a statistical match with a piece of equipment in the system.

Lets go into more depth of technology by understanding reference architecture of an IOT.

IOT Based – Reference architecture

1. Sensors – they process data from all the machines or asset to process further.
2. Field Gateway – They act as aggregators for all the sensor data and deposit them onto the cloud environment.
3. Cloud Gateway – Process those data and pass it to streaming data processors as the data velocity is high you need specialized streamers.
4. Data Lakes – Streaming data is now stored into lakes as transactional data.
5. Big Data Warehouses – The data stores where all the machine learning operations will be executed.
6. Machine Learning Algorithms – They continuously run on big data warehouses, if desired conditions are not met failure models are called.
7. Control Application – They do two things if there failure module is activated, first they trigger command to sensor to stop or hold working & second they notify maintenance system about the need of maintenance or failure.
8. Data Analytics – They are graphical or tabular dashboards for providing insights in the big data warehouses.
9. User Applications – Frontend application for users or operators.

Implementing reference architecture using AWS Technology Stack

Application in varied industries

Predictive maintenance by industries

Engineers across industries are now considering application of predictive maintenance. Teknonauts trying to list some possible applications from manufactures point of view.

Discrete manufacturing

Major discrete manufacturers are using predictive maintenance based on IoT to monitor, for example, the health of spindles in milling machines. They are prone to breaking, while their repair is expensive. An IoT-based predictive maintenance solution can help to predict potential damage by collecting data from ultrasonic and vibration sensors attached to the spindle.

Process manufacturing

In process manufacturing, pulp processing and paper manufacturing companies leverage IIoT to monitor the state of paper-making machines. For example, Maastricht Mill equipped their press rolls with temperature and vibration sensors and rolled out a cloud-based predictive maintenance solution to predict damages of bearings and gears.

Scheduling maintenance for a press roll based on a cover failure prediction

Another example is the steel industry. Steel plants have multiple furnaces that use water cooling panels to control temperature. Leakages in the panels may cause safety issues and production losses. An IoT-based predictive maintenance solution can help detect anomalies and carry out a root cause analysis, preventing production delays and equipment failures.

Oil and gas

Oil & gas companies particularly benefit from applying predictive maintenance solutions. Physical inspection of oil & gas production equipment requires personnel to go into hazardous environment to examine the equipment, which in some cases is not feasible. IoT-based predictive maintenance allows oil & gas companies to identify potential failures and increase the production of highly critical assets.

Electric power industry

Electric power plants have to ensure reliable power supply, particularly, during the periods of peak demand. An IoT-based maintenance solution can help to ensure uninterrupted power generation and detect evolving flaws in a gas/wind/steam turbine’s rotating components. For that, a turbine gets equipped with vibration sensors. The data collected by sensors is relayed to the cloud and run through ML algorithms to determine how each turbine performs.

Scheduling maintenance for a wind turbine based on a main bearing failure prediction

Railways

Railway companies apply IoT-based predictive maintenance to ensure the rails and the rolling stock are in proper condition. The solution helps to improve safety, reliability and velocity of the rolling stock, as well as reduce train delays caused by equipment malfunctions.

Construction

In construction, predictive maintenance is applied to monitor the state of heavy machinery, e.g. excavators, bulldozers, loaders, lifts, etc. Sensors can be attached to a machine to monitor transmission and brake temperature, engine RPM, tire pressure, fuel consumption and other values. The cloud identifies potential problems with exhaust after-treatment systems, as well as rotating and static components damages.

Conclusion

IoT-based predictive maintenance improves equipment’s life, helps to eliminate as much as 30 percent of the time-based maintenance routine, and reduces equipment downtime by 50 percent. For a mature and reliable predictive maintenance solution. Its better to start thinking now of it otherwise you would lack behind.

Do follow our Youtube channel for latest videos.

Explore more at Teknonauts

Ashish Kumar Singal

Ashish is technology freak with around 11+ years of experience in IT Landscape. He started his journey as a device driver programmer in 2010. From that point he has evolved as a Mobility and IOT Architect, he completed his M.Tech from BITS Pilani as System Architect. He is working as Principal Architect at Oracle currently.

linkedin.com/in/ashish-kumar-singal-0252812b

Tips for the course- AWS Solutions Architect Associate 

Take detailed notes and build an organized study guide.

• Use a Online course and download the lectures for offline listening. Play lectures and summaries over again while doing things like driving or walking your dog. My prep strategy involved a lot of daily immersion, like this.
• Do not skip the hands-on labs. In my opinion, using AWS is the best way to learn AWS and become AWS Solutions Architect. This will really help internalize the content from the lectures.

Strategy and Important Links

1. Complete Stephane Maarek course giving enough time to hands-on ( AWS Solutions Architect Associate )
   • https://www.udemy.com/course/aws-certified-solutions-architect-associate-saa-c02/
2. Give a practice test at end of the course and assess yourself on weak areas
3. Identify weak areas and refer to the below link to clear your doubts ( AWS Solutions Architect Associate )
   • https://d1.awsstatic.com/whitepapers/aws-building-fault-tolerant-applications.pdf
   • https://d1.awsstatic.com/whitepapers/Storage/AWS%20Storage%20Services%20Whitepaper-v9.pdf
   • https://digitalcloud.training/certification-training/aws-solutions-architect-associate/
4. Finally, give the below AWS Solutions Architect Associate practice test from Neal Davis and keep on giving until you start scoring more than 80%
   • https://www.udemy.com/course/aws-certified-solutions-architect-associate-practice-tests-k/

Snapshots of Services – Required for quick revision before AWS Solutions Architect Associate exam

1. Spot fleet instance help to launch mix of on demand & spot instances. If instance need to manage auto scaling fleet is a choice.
2. Elastic Fabric Adapter ~ high level of inter instance communication.
3. WAF ~ block common attack patterns, such as SQL injection or cross-site scripting, and rules that filter out specific traffic
4. NACL ~ NACLs are not associated with instances. NACL denies all traffic both inbound and outbound by default. NACLs are the preferred option for blocking specific IPs or ranges vs Security Group. However WAF can be preferred if in choice
5. Amazon S3 Transfer Acceleration ~ Can speed to & from transfer upto 50-500% from S3 for long distance & large object transfer.
6. AWS Shield ~for DDOS attack.
7. AWS Secrets Manager ~the service enables you to easily rotate, manage, and retrieve database credentials, API keys, and other secrets throughout their lifecycle.
8. AWS Key Management Service (KMS) ~create and manage cryptographic keys and control their use across a wide range of AWS services (Encrypt data in your applications).
9. AWS Systems Manager Parameter Store ~Parameter Store =storage for configuration data management. Can store password but you have to manage rotation.
10. CloudHSM– AWS CloudHSM is a cloud-based hardware security module (HSM) – easily generate and use your encryption keys. also an encryption service, not a secrets store.
11. Kinesis Data Firehose ~ reliably load streaming data into data lakes, data stores, and analytics tools.
12. Kinesis Data Streams ~ massively scalable and durable real-time data streaming service,=scale without limits via increasing the number of shards within a data stream (Kinesis Data Streams Fanout).
13. Kinesis Data Analytics– Is the easiest way to analyze streaming data in real-time
14. Amazon EMR – big data platform uses Hadoop.
15. Transit Gateway~ Interconnect your VPC and on-premises networks. star network.
16. VPN Gateway & VPN Connection & site-to-site VPN ~endpoint on the VPC side of your VPN connection [This is very important topic for AWS Solutions Architect exam].
17. Private Link ~ AWS Private Link provides private connectivity between VPCs, AWS services, and on-premises applications, securely on the Amazon network (cross account communication).
18. Resource Access manager ~ enables you to easily and securely share AWS resources with any AWS account or within your AWS Organization.
19. Elastic Fabric Adapter (EFA)– is a network device that you can attach to your Amazon EC2 instance to accelerate High Performance Computing (HPC).
20. “Elastic Network Adapter” – Elastic Network Adapter (ENA) devices support enhanced networking via single root I/O virtualization (SR-IOV) to provide high-performance networking capabilities.
21. AWS Managed Microsoft AD – provides multiple ways to use Amazon Cloud Directory and Microsoft Active Directory (AD) with other AWS services. You can also configure a trust relationship between AWS Managed Microsoft AD in the AWS Cloud and your existing on-premises Microsoft AD.
22. Snowball – transfer greater than 10 TB of data between your on-premises data centers and Amazon S3.
    1. AWS Snowmobile is an Exabyte-scale data transfer service used to move extremely large amounts of data to AWS. Snowmobile to migrate large datasets of 10PB or more in a single location.
23. VPC sharing (part of Resource Access Manager) allows multiple AWS accounts to create their application resources such as EC2 instances, RDS databases, Redshift clusters, and Lambda functions, into shared and centrally managed Amazon Virtual Private Clouds (VPCs)..
24. AWS Cloud Formation Stack Set extends the functionality of stacks by enabling you to create, update, or delete stacks across multiple accounts and regions with a single operation.
25. AWS Trusted Advisor is an online tool that draws upon best practices learned from AWS’s aggregated operational history of serving hundreds of thousands of AWS customers. ~ inspects your AWS environment and makes recommendations for saving money, improving system performance, or closing security gaps.
26. File Gateway -> File gateway provides virtual on-premises file server, which enables you to store and retrieve files as objects in Amazon S3. File gateway offers SMB or NFS-based access to data in Amazon S3.
27. VOLUME GATEWAY ~block-based volumes, Block storage – iSCSI based, gateway-cached and gateway-stored modes [You will get 5-6 solid questions in AWS Solutions Architect exam on this topic].
28. AWS Step Functions –-> AWS Step Functions lets you coordinate and orchestrate multiple AWS services such as AWS Lambda and AWS Glue into server less workflows.
29. LightSail –> easy-to-use cloud platform that offers you everything needed to build an application or website, plus a cost-effective, monthly plan.
30. VPN Cloud Hub –> Linked remote offices for backup. Need internet connection.
31. Data Sync -> AWS Data Sync is an online data transfer service that simplifies, automates, and accelerates copying large amounts of data to and from AWS storage services over the internet or AWS Direct Connect.
32. AWS CONFIG -> AWS resource inventory, configuration history, and configuration change notifications to enable security and governance.
33. Pilot Light –> describe a DR scenario in which a minimal version of an environment is always running in the cloud.
34. Service control policies (SCPs) –> are one type of policy that you can use to manage your organization. central control over the maximum available permissions for all accounts in your organization.
35. IAM Permission Boundary--> Support for IAM entities (users or roles)..
36. S3 Glacier Vault–> A vault is a container for storing archives.
37. S3 Glacier Vault Lock –> allows you to easily deploy and enforce compliance controls for individual S3 Glacier vaults with a vault lock policy.
38. AWS STORAGE GATEWAY –> hybrid storage between on-premises environments and the AWS Cloud. File Gateway :: NFS,SMB , Volume Gateway (Stored for asynchronous replication, cached for frequent access) ::iSCSI, Tape Gateway :: ISCSI( tape library existing backup).
39. Amazon DynamoDB and Amazon S3 support –> gateway endpoints ~ usages prefix lists in the route table to redirect traffic (security) |  using VPC endpoint policies.
40. All other interface endpoint (powered by Private Link – means a private IP) ~ use DNS entries to redirect traffic | Secure using security group.
41. Task Role–>   To specify permissions for a specific task on Amazon ECS you should use IAM Roles for Tasks.
42. Cool down period –->  Is a configurable setting for your Auto Scaling group that helps to ensure that it doesn’t launch or terminate additional instances before the previous scaling activity takes effect
43. AWS Global Accelerator –-> uses the vast, congestion-free AWS global network to route TCP and UDP traffic to a healthy application endpoint in the closest AWS Region to the user.
44. Virtual Private Gateway--> VPG is used to setup an AWS VPN which you can use in combination with Direct Connect to encrypt all data that traverses the Direct Connect link.
45. Amazon Redshift Enhanced VPC Routing —> provides VPC resource access to Redshift.
46. VPC Endpoints –> enable to privately connect your VPC to support AWS services & VPC endpoint services powered by Private Link (without IGW,NAT, VPN connection or Direct connection). Also, this configuration uses a NLB and can be fault-tolerant by configuring multiple subnets.
47. Always assign IAM roles to the EC2 instance to ensure secure access to AWS resources from EC2 instance.
48. Always need to keep NAT gateway on public subnet only because it needs to communicate the internet.
49. Amazon Kinesis makes it easy to collect , process & analyze real time streaming data.. Can ingest Realtime data, video, audio , application log, website clickstream, IOT telemetry data for machine learning, analytics and other applications.
50. Amazon ECS – use case Microservices & batch jobs.
51. Beanstalk –> AWS Elastic Beanstalk can be used to quickly deploy and manage applications in the AWS Cloud. Elastic beanstalk support the deployment of web application from docker container.
52. Fargate Launch Type –> The Fargate launch type allows you to run your containerized applications without the need to provision and manage the backend infrastructure. Just register your task definition and Fargate launches the container for you.
53. Cloud Formation – infrastructure as a code. Automate whole infrastructure.
54. SSE-S3 –> Amazon S3 manages the data & master encryption key.
55. SSE-C –> you manages the key.
56. SSE-KMS –> AWS manages data key but you manage master key in AWS KMS.
57. S3 select vs Athena.
58. Amazon DynamoDB global tables provide a fully managed solution for deploying a multi-region, multi-master database and provides an active-active configuration .
59. Amazon Aurora Global Database provides read access to a database in multiple regions – it does not provide active-active configuration with bi-directional synchronization

View acclaim for AWS Solution Architect Associate exam

Awadhesh Dwivedi and Ashish Singal

Conclusion

These are very simple steps but require your full and steady dedication to clear AWS Solutions Architect Associate exam. If you can follow regularly, you can clear AWS Solutions Architect Associate exam within couple of month’s time.

Learn more on AWS Solutions Architect at explore on Teknonauts.

Awadhesh Pratap Dwivedi

Awadhesh Pratap Dwivedi is an IT industry leader with over 13+ years of experience. He is excellent at providing an easy solution to complex business problems with his tremendous problem-solving skills. Currently, he is working with Oracle as a Principal Solution Engineer.

teknonauts.com/