import boto3, sys, datetime, socket def _get_boto_session(profile_name: str) -> boto3.Session: """ Get the boto3 session. Works with profile configured in runtime. :param profile_name: The configured AWS profile name. Pass in None to use default credentials chain. :returns: The Boto session. """ if profile_name == None: session = boto3.Session(region_name="ap-southeast-1") return session else: session = boto3.Session(profile_name=profile_name) return session def _check( session: boto3.Session, trainer_name: str, ): ret_and_indent = "
" step_2_needed = None # AWS pricing for SIN c5_xlarge_instance_minute_price = 0.003266666666666667 ebs_gp2_100gb_minute_price = 0.00023148148148148146 # AWS pricing for NRT c5_xlarge_instance_minute_price = 0.0035666666666666668 ebs_gp2_100gb_minute_price = 0.00023148148148148146 # AWS pricing for PAX c5_xlarge_instance_minute_price = 0.0028333333333333335 ebs_gp2_100gb_minute_price = 0.00023148148148148146 c5_xlarge_minute_price = ( c5_xlarge_instance_minute_price + ebs_gp2_100gb_minute_price ) ec2_client = session.client("ec2") sum_cost = 0.0 instances_dict = {} response = None real_reservations = [] if trainer_name == "all": response = ec2_client.describe_instances( Filters=[ { "Name": "instance-state-name", "Values": [ "running", ], }, ], DryRun=False, MaxResults=500, ) real_reservations += [response["Reservation"]] while "NextToken" in response and response["NextToken"] != None: nt = response["NextToken"] response = ec2_client.describe_instances( Filters=[ { "Name": "instance-state-name", "Values": [ "running", ], }, ], DryRun=False, MaxResults=500, NextToken=nt, ) real_reservations += [response["Reservation"]] else: response = ec2_client.describe_instances( Filters=[ { "Name": "instance-state-name", "Values": [ "running", ], }, { "Name": "tag:trainer", "Values": [ trainer_name, ], }, ], DryRun=False, MaxResults=500, ) real_reservations += [response["Reservations"]] while "NextToken" in response and response["NextToken"] != None: nt = response["NextToken"] response = ec2_client.describe_instances( Filters=[ { "Name": "instance-state-name", "Values": [ "running", ], }, { "Name": "tag:trainer", "Values": [ trainer_name, ], }, ], DryRun=False, MaxResults=500, NextToken=nt, ) real_reservations += [response["Reservations"]] for reservations in real_reservations: for reservation in reservations: for instances in reservation["Instances"]: up_time = round( ( datetime.datetime.now(datetime.timezone.utc) - instances["UsageOperationUpdateTime"] ).seconds / 60 ) name = None trainer = None student = None node_role = None for tag in instances["Tags"]: if tag["Key"] == "Name": name = tag["Value"] if tag["Key"] == "trainer": trainer = tag["Value"] if tag["Key"] == "student": student = tag["Value"] if tag["Key"] == "role": node_role = tag["Value"] if ( name == None or trainer == None or student == None or node_role == None ) and (name != "lab-control"): step_2_needed = "Setup In-Progress ..." cost = 0.0 cost = round(up_time * c5_xlarge_minute_price, 2) if name != "lab-control": sum_cost += cost instances_dict.update( { (trainer if trainer != None else " ") + ":" + (student if student != None else " ") + ":" + (node_role if node_role != None else " ") + ":" + instances["InstanceId"]: "" + instances["InstanceId"].rjust(19, " ") + "" + instances["PublicIpAddress"].ljust(16, " ") + "" + instances["PrivateIpAddress"].ljust(16, " ") + "" + (name.ljust(13, " ") if name != None else " ") + "" + (trainer.ljust(10, " ") if trainer != None else " ") + "" + (student.ljust(7, " ") if student != None else " ") + "" + (node_role.ljust(9, " ") if node_role != None else " ") + "" + str(up_time).ljust(14, " ") + "" } ) else: cost = str(cost) + " (covered by RI)" if step_2_needed != None: print("

" + step_2_needed + "

") trainer_name_cache = "NONE" student_name_cache = "NONE" for key in sorted([*instances_dict]): trainer_name = key.split(":")[0] student_name = key.split(":")[1] if trainer_name != trainer_name_cache or student_name != student_name_cache: print("") print("") print("") print( "" ) print("") print("") trainer_name_cache = trainer_name student_name_cache = student_name print(instances_dict[key]) print("") print("

", trainer_name, "可用的实验节点:
实例 ID	公网 IP	私网 IP	建议角色	讲师标签	学生标签	名称	启动时间 (分钟)

") m_public_ip = "monitor1_address" for key in sorted([*instances_dict]): trainer_name = key.split(":")[0] student_name = key.split(":")[1] trainer_name_cache = trainer_name student_name_cache = student_name row = instances_dict[key] if "monitor1" in row: m_public_ip = row.split("")[1].strip() print('

') print( "
信息收集于 - (UTC) " + str(datetime.datetime.now()), "实验环境拥有 ", str(len([*instances_dict])), " 个节点。
", ) if len([*instances_dict]) == 0: print( '

选择一个 "练习" 开始实验。

' ) if m_public_ip != "monitor1_address": print("

") if "None" not in pd_dashboard_url: print( '

    PD 仪表板 - '
                + pd_dashboard_url
                + "

" ) monitor_ip = m_public_ip.strip() grafana_port = 3000 timeout_seconds = 1 sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) sock.settimeout(timeout_seconds) result = sock.connect_ex((monitor_ip, int(grafana_port))) if result == 0: print( '

    Grafana 仪表板 - http://'
                + monitor_ip
                + ":3000

" ) sock.close() print("

") else: None print( '

    连接中控机的步骤：在环境准备就绪后，按照以下步骤登录中控机节点 monitor1 (更多详细信息或 Windows 笔记本电脑用户请参阅本指南)。

' ) print( '    1. 保护下载好的 TiUP 中控机私钥 (单击密钥文件名进行下载):     chmod 400 pe-class-key-singapore.pem
' ) print( '    2. 确保 ssh-agent 已经运行在您的笔记本上了 (Windows 用户请参阅本指南)。
' ) print( '    3. 将身份添加到身份验证代理:     ssh-add pe-class-key-singapore.pem
' ) print( '    4. SSH 登录到 TiUP 中控机:       ssh -A -o ServerAliveInterval=30 -o ServerAliveCountMax=5 ec2-user@' + m_public_ip + "
", ) print( '

课堂中基本的 TiDB 集群拓扑:

' ) print( '

' ) if __name__ == "__main__": trainer_name = sys.argv[1] pd_dashboard_url = sys.argv[2] session = _get_boto_session(None) _check(session, trainer_name)