I am trying to sync two S3 buckets in different accounts. I have successfully configured the locations and created a task. However, when I run the task I get a Unable to connect to S3 endpoint error. Can anyone help?
This could have been related to the datasync's IAM role's policy (datasync IAM role) not having permission to the target S3 bucket
verify your policy and trust relationship using the below documentation
https://docs.aws.amazon.com/datasync/latest/userguide/using-identity-based-policies.html
Also turn on cloudwatch logs (like shown in the image) and view detailed log in cloudwatch. If it is permission related, add the missing policy in the Datasync role.
Related
I am trying to register a respository on AWS S3 to store ElasticSearch snapshots.
I am following guide and ran the very first command listed in the doc.
But I am getting the error Access Denied while executing that command.
The role that is being used to perform operations on S3 is the AmazonEKSNodeRole.
I have assigned the appropriate permissions to the role to perform operations on the S3 bucket.
Also, here is another doc which suggests to use kibana for ElasticSearch version > 7.2 but I am doing the same via cURL requests.
Below is trust Policy of the role through which I am making the request to register repository in the S3 bucket.
Also, below are the screenshots of the permissions of the trusting and trusted accounts respectively -
I am trying to use my bucket to give the arguments for the EMR to create a cluster for it is giving me "All access to this object has been disabled (Service: Amazon S3; Status Code: 403; Error Code: AllAccessDisabled;"
I have used my Reducer and Mapper python files and my bucket's permission is public too
is there something wrong with my mapper and reducer files or am I missing a trick here
Make sure you've assigned your EMR cluster an IAM role that has adequate S3 access permissions. IAM enables you to grant permissions to users, groups, or resources (like your EMR cluster, in this instance) to be able to access other services or resources in AWS (like S3, which is currently giving you an access denied error).
To do this through EMRFS:
Navigate to the EMR console
click Security configurations (on left menu)
Scroll down to IAM roles for EMRFS
Enable Use IAM roles for EMRFS requests to Amazon S3
Add role mapping
Select desired IAM role (Admin)
Select whatever basis for access you prefer (User, group, or S3 bucket name prefix)
Here's a pic of what it looks like in console:
More on this available in the docs here: https://docs.aws.amazon.com/emr/latest/ManagementGuide/emr-iam-roles.html
https://docs.aws.amazon.com/emr/latest/ManagementGuide/emr-emrfs-iam-roles.html
I have a HDP cluster on AWS and I have one s3(in other account) also, my hadoop version is Hadoop 3.1.1.3.0.1.0-187
Now I want to read from the s3 (which is in different account) and process, then write the result to my s3(same account as cluster).
But as per the HDP guide Here tells, I can configure only one keys of either my account or other account.
But in my case I want to configure two account keys, so How to do do that ?
Due to some security reason, other account can not change the bucket policy to add IAM role which is created in my account , Hence I tried to access like below
Configured the keys of other account
Added IAM role(which has access policy for my bucket) of my account
but Still I got below error when I tried to access my account s3 from spark write
com.amazonaws.services.s3.model.AmazonS3Exception: Status Code: 400, AWS Service: Amazon S3
What you need is to use the EC2 instance profile role. It is an IAM role that is attached to your instance: https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles_use_switch-role-ec2_instance-profiles.html
You first create a role with permissions that allow s3 access. Then you attach that role to your HDP cluster(EC2 autoscaling group and EMR can both achieve that).No IAM access key configuration needed on your side, although AWS still does that for you in the background. This is the s3 "outbound" access part.
The 2nd step is to set up the bucket policy to allow cross-account access: https://docs.aws.amazon.com/AmazonS3/latest/dev/example-walkthroughs-managing-access-example2.html
You will need to do this for each bucket in your different accounts. This is basically the "inbound" s3 access permission part.
You will encounter 400 if any part of your access(i.e., your instance profile role's permission, S3 bucket ACL, bucket policy, public access block setting and etc..) is denied in the permission chain. There are much more layers on the "inbound" side. So to start to get things working, if you are not IAM expert, try to start with a very open policy(use '*' wildcard) and then narrow things down.
If I've understood right
you want your EC2 VMs to access an S3 bucket to which the IAM role doesn't have access
your have a set of AWS login details for the external S3 bucket (login and password)
HDP3 has an default auth chain of, in order
per-bucket secrets. fs.s3a.bucket.NAME.access.key, fs.s3a.bucket.NAME.secret.key
config-wide secrets fs.s3a.access.key, fs.s3a.secret.key
env vars AWS_ACCESS_KEY and AWS_SECRET_KEY
the IAM Role (it does an HTTP GET to the 169.something server which serves up a new set of IAM role credentials at least once an hour)
What you need to try here is set up some per-bucket secrets for only the external source (either in a JCEKS file on all nodes in core-site.xml, or in the spark default. For example, if the external bucket was s3a://external, you'd have
spark.hadoop.fs.s3a.bucket.external.access.key AKAISOMETHING spark.hadoop.fs.s3a.bucket.external.secret.key SECRETSOMETHING
HDP3/Hadoop 3 can handle >1 secret in the same JCEKS file without problems. HADOOP-14507. my code. Older versions let you put username:secret in the URI, but that's such a security troublespot (everything logs those URIs as they aren't viewed as sensistive), that feature has been cut from Hadoop now. Stick to the JCEKs file with a per-bucket secret, falling back to IAM role for your own data
Note you can fiddle with the authentication list for ordering and behaviour: if you add use the TemporaryAWSCredentialsProvider then it'll support session keys as well, which is often handy.
<property>
<name>fs.s3a.aws.credentials.provider</name>
<value>
org.apache.hadoop.fs.s3a.TemporaryAWSCredentialsProvider,
org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider,
com.amazonaws.auth.EnvironmentVariableCredentialsProvider,
org.apache.hadoop.fs.s3a.auth.IAMInstanceCredentialsProvider
</value>
</property>
I am currently trying to enable AWS Config notifications on multiple accounts. I have enabled monitoring on each individual account with its own S3 bucket and SNS topic, but it would make more sense to have one centralized bucket and topic. I am trying to implement this with little success.
I have created an s3 bucket and target ARN but when I try and apply the changes I get an error of insufficient delivery policy
Note I am doing this through the AWS console and not with code.
To do this, you need two pieces:
The Identity and Access Management (IAM) Role being used must have permissions to deliver data to the common S3 bucket and SNS Topic. You'll need to go to the IAM Management Console, and edit the role being used by Config in each account and update the S3 bucket/SNS names in "PutObject", "GetBucketACL" and "sns:Publish"
You also need to allow the S3 bucket and SNS Topic to receive data from this new role. See
a. http://docs.aws.amazon.com/awscloudtrail/latest/userguide/aggregating_logs_accounts_bucket_policy.html
b. http://docs.aws.amazon.com/sns/latest/dg/AccessPolicyLanguage_UseCases_Sns.html
I have a question on using IAM roles with EC2 and EMR. Here's my current setup:
I have a EC2 machine launched with a particular IAM role (let's call this role 'admin'). My workflow is to upload a file to S3 from this machine and then create an EMR cluster with a particular IAM role (a 'runner' role). The EMR cluster works on the file uploaded to S3 from the admin machine.
Admin is a role with privileges to all APIs in all AWS services. Runner has access to all APIs in EMR, EC2 and S3.
For some reason, the EMR cluster is unable to access the input file loaded in S3. It keeps getting an 'access denied' exception from s3.
I guess writing to s3 from one IAM role and reading it from a different IAM role is what is causing the issue.
Any ideas on what is going wrong here or whether this is even a supported use-case is appreciated.
Thanks!
http://blogs.aws.amazon.com/security/post/TxPOJBY6FE360K/IAM-policies-and-Bucket-Policies-and-ACLs-Oh-My-Controlling-Access-to-S3-Resourc
S3 objects are protected in three ways as seen in the post I linked to.
Your IAM role will need the permission to read S3 objects.
The S3 bucket policy must allow your IAM role access to the object.
The S3 ACL for the specific object must also allow your IAM role access to the object.